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From l..@apache.org
Subject svn commit: r959803 [31/32] - in /websites/production/commons/content/proper/commons-math: jacoco/ jacoco/org.apache.commons.math3.fraction/ jacoco/org.apache.commons.math3.genetics/ jacoco/org.apache.commons.math3.geometry.euclidean.threed/ jacoco/org...
Date Mon, 27 Jul 2015 19:42:10 GMT
Modified: websites/production/commons/content/proper/commons-math/xref-test/org/apache/commons/math3/stat/inference/KolmogorovSmirnovTestTest.html
==============================================================================
--- websites/production/commons/content/proper/commons-math/xref-test/org/apache/commons/math3/stat/inference/KolmogorovSmirnovTestTest.html (original)
+++ websites/production/commons/content/proper/commons-math/xref-test/org/apache/commons/math3/stat/inference/KolmogorovSmirnovTestTest.html Mon Jul 27 19:42:09 2015
@@ -25,332 +25,332 @@
 <a class="jxr_linenumber" name="L17" href="#L17">17</a>  
 <a class="jxr_linenumber" name="L18" href="#L18">18</a>  <strong class="jxr_keyword">package</strong> org.apache.commons.math3.stat.inference;
 <a class="jxr_linenumber" name="L19" href="#L19">19</a>  
-<a class="jxr_linenumber" name="L20" href="#L20">20</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.distribution.NormalDistribution;
-<a class="jxr_linenumber" name="L21" href="#L21">21</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.distribution.UniformRealDistribution;
-<a class="jxr_linenumber" name="L22" href="#L22">22</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.random.Well19937c;
-<a class="jxr_linenumber" name="L23" href="#L23">23</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.util.FastMath;
-<a class="jxr_linenumber" name="L24" href="#L24">24</a>  <strong class="jxr_keyword">import</strong> org.junit.Assert;
-<a class="jxr_linenumber" name="L25" href="#L25">25</a>  <strong class="jxr_keyword">import</strong> org.junit.Test;
-<a class="jxr_linenumber" name="L26" href="#L26">26</a>  
-<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em class="jxr_javadoccomment"> * Test cases for {@link KolmogorovSmirnovTest}.</em>
-<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em class="jxr_javadoccomment"> * @since 3.3</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em class="jxr_javadoccomment"> */</em>
-<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> <a href="../../../../../../org/apache/commons/math3/stat/inference/KolmogorovSmirnovTestTest.html">KolmogorovSmirnovTestTest</a> {
-<a class="jxr_linenumber" name="L33" href="#L33">33</a>  
-<a class="jxr_linenumber" name="L34" href="#L34">34</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> TOLERANCE = 10e-10;
-<a class="jxr_linenumber" name="L35" href="#L35">35</a>  
-<a class="jxr_linenumber" name="L36" href="#L36">36</a>      <em class="jxr_comment">// Random N(0,1) values generated using R rnorm</em>
-<a class="jxr_linenumber" name="L37" href="#L37">37</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] gaussian = {
-<a class="jxr_linenumber" name="L38" href="#L38">38</a>          0.26055895, -0.63665233, 1.51221323, 0.61246988, -0.03013003, -1.73025682, -0.51435805, 0.70494168, 0.18242945,
-<a class="jxr_linenumber" name="L39" href="#L39">39</a>          0.94734336, -0.04286604, -0.37931719, -1.07026403, -2.05861425, 0.11201862, 0.71400136, -0.52122185,
-<a class="jxr_linenumber" name="L40" href="#L40">40</a>          -0.02478725, -1.86811649, -1.79907688, 0.15046279, 1.32390193, 1.55889719, 1.83149171, -0.03948003,
-<a class="jxr_linenumber" name="L41" href="#L41">41</a>          -0.98579207, -0.76790540, 0.89080682, 0.19532153, 0.40692841, 0.15047336, -0.58546562, -0.39865469, 0.77604271,
-<a class="jxr_linenumber" name="L42" href="#L42">42</a>          -0.65188221, -1.80368554, 0.65273365, -0.75283102, -1.91022150, -0.07640869, -1.08681188, -0.89270600,
-<a class="jxr_linenumber" name="L43" href="#L43">43</a>          2.09017508, 0.43907981, 0.10744033, -0.70961218, 1.15707300, 0.44560525, -2.04593349, 0.53816843, -0.08366640,
-<a class="jxr_linenumber" name="L44" href="#L44">44</a>          0.24652218, 1.80549401, -0.99220707, -1.14589408, -0.27170290, -0.49696855, 0.00968353, -1.87113545,
-<a class="jxr_linenumber" name="L45" href="#L45">45</a>          -1.91116529, 0.97151891, -0.73576115, -0.59437029, 0.72148436, 0.01747695, -0.62601157, -1.00971538,
-<a class="jxr_linenumber" name="L46" href="#L46">46</a>          -1.42691397, 1.03250131, -0.30672627, -0.15353992, -1.19976069, -0.68364218, 0.37525652, -0.46592881,
-<a class="jxr_linenumber" name="L47" href="#L47">47</a>          -0.52116168, -0.17162202, 1.04679215, 0.25165971, -0.04125231, -0.23756244, -0.93389975, 0.75551407,
-<a class="jxr_linenumber" name="L48" href="#L48">48</a>          0.08347445, -0.27482228, -0.4717632, -0.1867746, -0.1166976, 0.5763333, 0.1307952, 0.7630584, -0.3616248,
-<a class="jxr_linenumber" name="L49" href="#L49">49</a>          2.1383790, -0.7946630, 0.0231885, 0.7919195, 1.6057144, -0.3802508, 0.1229078, 1.5252901, -0.8543149, 0.3025040
-<a class="jxr_linenumber" name="L50" href="#L50">50</a>      };
-<a class="jxr_linenumber" name="L51" href="#L51">51</a>  
-<a class="jxr_linenumber" name="L52" href="#L52">52</a>      <em class="jxr_comment">// Random N(0, 1.6) values generated using R rnorm</em>
-<a class="jxr_linenumber" name="L53" href="#L53">53</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] gaussian2 = {
-<a class="jxr_linenumber" name="L54" href="#L54">54</a>          2.88041498038308, -0.632349445671017, 0.402121295225571, 0.692626364613243, 1.30693446815426,
-<a class="jxr_linenumber" name="L55" href="#L55">55</a>          -0.714176317131286, -0.233169206599583, 1.09113298322107, -1.53149079994305, 1.23259966205809,
-<a class="jxr_linenumber" name="L56" href="#L56">56</a>          1.01389927412503, 0.0143898711497477, -0.512813545447559, 2.79364360835469, 0.662008875538092,
-<a class="jxr_linenumber" name="L57" href="#L57">57</a>          1.04861546834788, -0.321280099931466, 0.250296656278743, 1.75820367603736, -2.31433523590905,
-<a class="jxr_linenumber" name="L58" href="#L58">58</a>          -0.462694696086403, 0.187725700950191, -2.24410950019152, 2.83473751105445, 0.252460174391016,
-<a class="jxr_linenumber" name="L59" href="#L59">59</a>          1.39051945380281, -1.56270144203134, 0.998522814471644, -1.50147469080896, 0.145307533554146,
-<a class="jxr_linenumber" name="L60" href="#L60">60</a>          0.469089457043406, -0.0914780723809334, -0.123446939266548, -0.610513388160565, -3.71548343891957,
-<a class="jxr_linenumber" name="L61" href="#L61">61</a>          -0.329577317349478, -0.312973794075871, 2.02051909758923, 2.85214308266271, 0.0193222002327237,
-<a class="jxr_linenumber" name="L62" href="#L62">62</a>          -0.0322422268266562, 0.514736012106768, 0.231484953375887, -2.22468798953629, 1.42197716075595,
-<a class="jxr_linenumber" name="L63" href="#L63">63</a>          2.69988043856357, 0.0443757119128293, 0.721536984407798, -0.0445688839903234, -0.294372724550705,
-<a class="jxr_linenumber" name="L64" href="#L64">64</a>          0.234041580912698, -0.868973119365727, 1.3524893453845, -0.931054600134503, -0.263514296006792,
-<a class="jxr_linenumber" name="L65" href="#L65">65</a>          0.540949457402918, -0.882544288773685, -0.34148675747989, 1.56664494810034, 2.19850536566584,
-<a class="jxr_linenumber" name="L66" href="#L66">66</a>          -0.667972122928022, -0.70889669526203, -0.00251758193079668, 2.39527162977682, -2.7559594317269,
-<a class="jxr_linenumber" name="L67" href="#L67">67</a>          -0.547393502656671, -2.62144031572617, 2.81504147017922, -1.02036850201042, -1.00713927602786,
-<a class="jxr_linenumber" name="L68" href="#L68">68</a>          -0.520197775122254, 1.00625480138649, 2.46756916531313, 1.64364743727799, 0.704545210648595,
-<a class="jxr_linenumber" name="L69" href="#L69">69</a>          -0.425885789416992, -1.78387854908546, -0.286783886710481, 0.404183648369076, -0.369324280845769,
-<a class="jxr_linenumber" name="L70" href="#L70">70</a>          -0.0391185138840443, 2.41257787857293, 2.49744281317859, -0.826964496939021, -0.792555379958975,
-<a class="jxr_linenumber" name="L71" href="#L71">71</a>          1.81097685787403, -0.475014580016638, 1.23387615291805, 0.646615294802053, 1.88496377454523, 1.20390698380814,
-<a class="jxr_linenumber" name="L72" href="#L72">72</a>          -0.27812153371728, 2.50149494533101, 0.406964323253817, -1.72253451309982, 1.98432494184332, 2.2223658560333,
-<a class="jxr_linenumber" name="L73" href="#L73">73</a>          0.393086362404685, -0.504073151377089, -0.0484610869883821
-<a class="jxr_linenumber" name="L74" href="#L74">74</a>      };
-<a class="jxr_linenumber" name="L75" href="#L75">75</a>  
-<a class="jxr_linenumber" name="L76" href="#L76">76</a>      <em class="jxr_comment">// Random uniform (0, 1) generated using R runif</em>
-<a class="jxr_linenumber" name="L77" href="#L77">77</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] uniform = {
-<a class="jxr_linenumber" name="L78" href="#L78">78</a>          0.7930305, 0.6424382, 0.8747699, 0.7156518, 0.1845909, 0.2022326, 0.4877206, 0.8928752, 0.2293062, 0.4222006,
-<a class="jxr_linenumber" name="L79" href="#L79">79</a>          0.1610459, 0.2830535, 0.9946345, 0.7329499, 0.26411126, 0.87958133, 0.29827437, 0.39185988, 0.38351185,
-<a class="jxr_linenumber" name="L80" href="#L80">80</a>          0.36359611, 0.48646472, 0.05577866, 0.56152250, 0.52672013, 0.13171783, 0.95864085, 0.03060207, 0.33514887,
-<a class="jxr_linenumber" name="L81" href="#L81">81</a>          0.72508148, 0.38901437, 0.9978665, 0.5981300, 0.1065388, 0.7036991, 0.1071584, 0.4423963, 0.1107071, 0.6437221,
-<a class="jxr_linenumber" name="L82" href="#L82">82</a>          0.58523872, 0.05044634, 0.65999539, 0.37367260, 0.73270024, 0.47473755, 0.74661163, 0.50765549, 0.05377347,
-<a class="jxr_linenumber" name="L83" href="#L83">83</a>          0.40998009, 0.55235182, 0.21361998, 0.63117971, 0.18109222, 0.89153510, 0.23203248, 0.6177106, 0.6856418,
-<a class="jxr_linenumber" name="L84" href="#L84">84</a>          0.2158557, 0.9870501, 0.2036914, 0.2100311, 0.9065020, 0.7459159, 0.56631790, 0.06753629, 0.39684629,
-<a class="jxr_linenumber" name="L85" href="#L85">85</a>          0.52504615, 0.14199103, 0.78551120, 0.90503321, 0.80452362, 0.9960115, 0.8172592, 0.5831134, 0.8794187,
-<a class="jxr_linenumber" name="L86" href="#L86">86</a>          0.2021501, 0.2923505, 0.9561824, 0.8792248, 0.85201008, 0.02945562, 0.26200374, 0.11382818, 0.17238856,
-<a class="jxr_linenumber" name="L87" href="#L87">87</a>          0.36449473, 0.69688273, 0.96216330, 0.4859432, 0.4503438, 0.1917656, 0.8357845, 0.9957812, 0.4633570,
-<a class="jxr_linenumber" name="L88" href="#L88">88</a>          0.8654599, 0.4597996, 0.68190289, 0.58887855, 0.09359396, 0.98081979, 0.73659533, 0.89344777, 0.18903099,
-<a class="jxr_linenumber" name="L89" href="#L89">89</a>          0.97660425
-<a class="jxr_linenumber" name="L90" href="#L90">90</a>      };
-<a class="jxr_linenumber" name="L91" href="#L91">91</a>  
-<a class="jxr_linenumber" name="L92" href="#L92">92</a>      <em class="jxr_javadoccomment">/** Unit normal distribution, unit normal data */</em>
-<a class="jxr_linenumber" name="L93" href="#L93">93</a>      @Test
-<a class="jxr_linenumber" name="L94" href="#L94">94</a>      <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianGaussian() {
-<a class="jxr_linenumber" name="L95" href="#L95">95</a>          <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L96" href="#L96">96</a>          <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
-<a class="jxr_linenumber" name="L97" href="#L97">97</a>          <em class="jxr_comment">// Uncomment to run exact test - takes about a minute. Same value is used in R tests and for</em>
-<a class="jxr_linenumber" name="L98" href="#L98">98</a>          <em class="jxr_comment">// approx.</em>
-<a class="jxr_linenumber" name="L99" href="#L99">99</a>          <em class="jxr_comment">// Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, gaussian,</em>
-<a class="jxr_linenumber" name="L100" href="#L100">100</a>         <em class="jxr_comment">// true), TOLERANCE);</em>
-<a class="jxr_linenumber" name="L101" href="#L101">101</a>         Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, gaussian, false), TOLERANCE);
-<a class="jxr_linenumber" name="L102" href="#L102">102</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
-<a class="jxr_linenumber" name="L103" href="#L103">103</a>         Assert.assertEquals(0.0932947561266756, test.kolmogorovSmirnovStatistic(unitNormal, gaussian), TOLERANCE);
-<a class="jxr_linenumber" name="L104" href="#L104">104</a>     }
-<a class="jxr_linenumber" name="L105" href="#L105">105</a> 
-<a class="jxr_linenumber" name="L106" href="#L106">106</a>     <em class="jxr_javadoccomment">/** Unit normal distribution, unit normal data, small dataset */</em>
-<a class="jxr_linenumber" name="L107" href="#L107">107</a>     @Test
-<a class="jxr_linenumber" name="L108" href="#L108">108</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianGaussianSmallSample() {
-<a class="jxr_linenumber" name="L109" href="#L109">109</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L110" href="#L110">110</a>         <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
-<a class="jxr_linenumber" name="L111" href="#L111">111</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[50];
-<a class="jxr_linenumber" name="L112" href="#L112">112</a>         System.arraycopy(gaussian, 0, shortGaussian, 0, 50);
-<a class="jxr_linenumber" name="L113" href="#L113">113</a>         Assert.assertEquals(0.683736463728347, test.kolmogorovSmirnovTest(unitNormal, shortGaussian, false), TOLERANCE);
-<a class="jxr_linenumber" name="L114" href="#L114">114</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
-<a class="jxr_linenumber" name="L115" href="#L115">115</a>         Assert.assertEquals(0.09820779969463278, test.kolmogorovSmirnovStatistic(unitNormal, shortGaussian), TOLERANCE);
-<a class="jxr_linenumber" name="L116" href="#L116">116</a>     }
-<a class="jxr_linenumber" name="L117" href="#L117">117</a> 
-<a class="jxr_linenumber" name="L118" href="#L118">118</a>     <em class="jxr_javadoccomment">/** Unit normal distribution, uniform data */</em>
-<a class="jxr_linenumber" name="L119" href="#L119">119</a>     @Test
-<a class="jxr_linenumber" name="L120" href="#L120">120</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianUniform() {
-<a class="jxr_linenumber" name="L121" href="#L121">121</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L122" href="#L122">122</a>         <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
-<a class="jxr_linenumber" name="L123" href="#L123">123</a>         <em class="jxr_comment">// Uncomment to run exact test - takes a long time. Same value is used in R tests and for</em>
-<a class="jxr_linenumber" name="L124" href="#L124">124</a>         <em class="jxr_comment">// approx.</em>
-<a class="jxr_linenumber" name="L125" href="#L125">125</a>         <em class="jxr_comment">// Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, uniform,</em>
-<a class="jxr_linenumber" name="L126" href="#L126">126</a>         <em class="jxr_comment">// true), TOLERANCE);</em>
-<a class="jxr_linenumber" name="L127" href="#L127">127</a>         Assert.assertEquals(8.881784197001252E-16, test.kolmogorovSmirnovTest(unitNormal, uniform, false), TOLERANCE);
-<a class="jxr_linenumber" name="L128" href="#L128">128</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
-<a class="jxr_linenumber" name="L129" href="#L129">129</a>         Assert.assertEquals(0.5117493931609258, test.kolmogorovSmirnovStatistic(unitNormal, uniform), TOLERANCE);
-<a class="jxr_linenumber" name="L130" href="#L130">130</a>     }
-<a class="jxr_linenumber" name="L131" href="#L131">131</a> 
-<a class="jxr_linenumber" name="L132" href="#L132">132</a>     <em class="jxr_javadoccomment">/** Uniform distribution, uniform data */</em>
-<a class="jxr_linenumber" name="L133" href="#L133">133</a>     <em class="jxr_comment">// @Test - takes about 6 seconds, uncomment for</em>
-<a class="jxr_linenumber" name="L134" href="#L134">134</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformUniform() {
-<a class="jxr_linenumber" name="L135" href="#L135">135</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L136" href="#L136">136</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
-<a class="jxr_linenumber" name="L137" href="#L137">137</a>         Assert.assertEquals(8.881784197001252E-16, test.kolmogorovSmirnovTest(unif, uniform, false), TOLERANCE);
-<a class="jxr_linenumber" name="L138" href="#L138">138</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, uniform, 0.05));
-<a class="jxr_linenumber" name="L139" href="#L139">139</a>         Assert.assertEquals(0.5400666982352942, test.kolmogorovSmirnovStatistic(unif, uniform), TOLERANCE);
-<a class="jxr_linenumber" name="L140" href="#L140">140</a>     }
-<a class="jxr_linenumber" name="L141" href="#L141">141</a> 
-<a class="jxr_linenumber" name="L142" href="#L142">142</a>     <em class="jxr_javadoccomment">/** Uniform distribution, uniform data, small dataset */</em>
-<a class="jxr_linenumber" name="L143" href="#L143">143</a>     @Test
-<a class="jxr_linenumber" name="L144" href="#L144">144</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformUniformSmallSample() {
-<a class="jxr_linenumber" name="L145" href="#L145">145</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L146" href="#L146">146</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
-<a class="jxr_linenumber" name="L147" href="#L147">147</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortUniform = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[20];
-<a class="jxr_linenumber" name="L148" href="#L148">148</a>         System.arraycopy(uniform, 0, shortUniform, 0, 20);
-<a class="jxr_linenumber" name="L149" href="#L149">149</a>         Assert.assertEquals(4.117594598618268E-9, test.kolmogorovSmirnovTest(unif, shortUniform, false), TOLERANCE);
-<a class="jxr_linenumber" name="L150" href="#L150">150</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, shortUniform, 0.05));
-<a class="jxr_linenumber" name="L151" href="#L151">151</a>         Assert.assertEquals(0.6610459, test.kolmogorovSmirnovStatistic(unif, shortUniform), TOLERANCE);
-<a class="jxr_linenumber" name="L152" href="#L152">152</a>     }
-<a class="jxr_linenumber" name="L153" href="#L153">153</a> 
-<a class="jxr_linenumber" name="L154" href="#L154">154</a>     <em class="jxr_javadoccomment">/** Uniform distribution, unit normal dataset */</em>
-<a class="jxr_linenumber" name="L155" href="#L155">155</a>     @Test
-<a class="jxr_linenumber" name="L156" href="#L156">156</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformGaussian() {
-<a class="jxr_linenumber" name="L157" href="#L157">157</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L158" href="#L158">158</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
-<a class="jxr_linenumber" name="L159" href="#L159">159</a>         <em class="jxr_comment">// Value was obtained via exact test, validated against R. Running exact test takes a long</em>
-<a class="jxr_linenumber" name="L160" href="#L160">160</a>         <em class="jxr_comment">// time.</em>
-<a class="jxr_linenumber" name="L161" href="#L161">161</a>         Assert.assertEquals(4.9405812774239166E-11, test.kolmogorovSmirnovTest(unif, gaussian, false), TOLERANCE);
-<a class="jxr_linenumber" name="L162" href="#L162">162</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, gaussian, 0.05));
-<a class="jxr_linenumber" name="L163" href="#L163">163</a>         Assert.assertEquals(0.3401058049019608, test.kolmogorovSmirnovStatistic(unif, gaussian), TOLERANCE);
-<a class="jxr_linenumber" name="L164" href="#L164">164</a>     }
-<a class="jxr_linenumber" name="L165" href="#L165">165</a> 
-<a class="jxr_linenumber" name="L166" href="#L166">166</a>     <em class="jxr_javadoccomment">/** Small samples - exact p-value, checked against R */</em>
-<a class="jxr_linenumber" name="L167" href="#L167">167</a>     @Test
-<a class="jxr_linenumber" name="L168" href="#L168">168</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleSmallSampleExact() {
-<a class="jxr_linenumber" name="L169" href="#L169">169</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L170" href="#L170">170</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] smallSample1 = {
-<a class="jxr_linenumber" name="L171" href="#L171">171</a>             6, 7, 9, 13, 19, 21, 22, 23, 24
-<a class="jxr_linenumber" name="L172" href="#L172">172</a>         };
-<a class="jxr_linenumber" name="L173" href="#L173">173</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] smallSample2 = {
-<a class="jxr_linenumber" name="L174" href="#L174">174</a>             10, 11, 12, 16, 20, 27, 28, 32, 44, 54
-<a class="jxr_linenumber" name="L175" href="#L175">175</a>         };
-<a class="jxr_linenumber" name="L176" href="#L176">176</a>         <em class="jxr_comment">// Reference values from R, version 2.15.3 - R uses non-strict inequality in null hypothesis</em>
-<a class="jxr_linenumber" name="L177" href="#L177">177</a>         Assert
-<a class="jxr_linenumber" name="L178" href="#L178">178</a>             .assertEquals(0.105577085453247, test.kolmogorovSmirnovTest(smallSample1, smallSample2, false), TOLERANCE);
-<a class="jxr_linenumber" name="L179" href="#L179">179</a>         Assert.assertEquals(0.5, test.kolmogorovSmirnovStatistic(smallSample1, smallSample2), TOLERANCE);
-<a class="jxr_linenumber" name="L180" href="#L180">180</a>     }
-<a class="jxr_linenumber" name="L181" href="#L181">181</a> 
-<a class="jxr_linenumber" name="L182" href="#L182">182</a>     <em class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L183" href="#L183">183</a> <em class="jxr_javadoccomment">     * Checks exact p-value computations using critical values from Table 9 in V.K Rohatgi, An</em>
-<a class="jxr_linenumber" name="L184" href="#L184">184</a> <em class="jxr_javadoccomment">     * Introduction to Probability and Mathematical Statistics, Wiley, 1976, ISBN 0-471-73135-8.</em>
-<a class="jxr_linenumber" name="L185" href="#L185">185</a> <em class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L186" href="#L186">186</a>     @Test
-<a class="jxr_linenumber" name="L187" href="#L187">187</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleExactP() {
-<a class="jxr_linenumber" name="L188" href="#L188">188</a>         checkExactTable(4, 6, 5d / 6d, 0.01d);
-<a class="jxr_linenumber" name="L189" href="#L189">189</a>         checkExactTable(4, 7, 17d / 28d, 0.2d);
-<a class="jxr_linenumber" name="L190" href="#L190">190</a>         checkExactTable(6, 7, 29d / 42d, 0.05d);
-<a class="jxr_linenumber" name="L191" href="#L191">191</a>         checkExactTable(4, 10, 7d / 10d, 0.05d);
-<a class="jxr_linenumber" name="L192" href="#L192">192</a>         checkExactTable(5, 15, 11d / 15d, 0.02d);
-<a class="jxr_linenumber" name="L193" href="#L193">193</a>         checkExactTable(9, 10, 31d / 45d, 0.01d);
-<a class="jxr_linenumber" name="L194" href="#L194">194</a>         checkExactTable(7, 10, 43d / 70d, 0.05d);
-<a class="jxr_linenumber" name="L195" href="#L195">195</a>     }
-<a class="jxr_linenumber" name="L196" href="#L196">196</a> 
-<a class="jxr_linenumber" name="L197" href="#L197">197</a>     @Test
-<a class="jxr_linenumber" name="L198" href="#L198">198</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleApproximateCritialValues() {
-<a class="jxr_linenumber" name="L199" href="#L199">199</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = .01;
-<a class="jxr_linenumber" name="L200" href="#L200">200</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] alpha = {
-<a class="jxr_linenumber" name="L201" href="#L201">201</a>             0.10, 0.05, 0.025, 0.01, 0.005, 0.001
-<a class="jxr_linenumber" name="L202" href="#L202">202</a>         };
-<a class="jxr_linenumber" name="L203" href="#L203">203</a>         <em class="jxr_comment">// From Wikipedia KS article - TODO: get (and test) more precise values</em>
-<a class="jxr_linenumber" name="L204" href="#L204">204</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] c = {
-<a class="jxr_linenumber" name="L205" href="#L205">205</a>             1.22, 1.36, 1.48, 1.63, 1.73, 1.95
+<a class="jxr_linenumber" name="L20" href="#L20">20</a>  <strong class="jxr_keyword">import</strong> java.util.Arrays;
+<a class="jxr_linenumber" name="L21" href="#L21">21</a>  
+<a class="jxr_linenumber" name="L22" href="#L22">22</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.distribution.NormalDistribution;
+<a class="jxr_linenumber" name="L23" href="#L23">23</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.distribution.UniformRealDistribution;
+<a class="jxr_linenumber" name="L24" href="#L24">24</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.random.RandomGenerator;
+<a class="jxr_linenumber" name="L25" href="#L25">25</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.random.Well19937c;
+<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.util.CombinatoricsUtils;
+<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <strong class="jxr_keyword">import</strong> org.apache.commons.math3.util.FastMath;
+<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <strong class="jxr_keyword">import</strong> org.junit.Assert;
+<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <strong class="jxr_keyword">import</strong> org.junit.Test;
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em class="jxr_javadoccomment"> * Test cases for {@link KolmogorovSmirnovTest}.</em>
+<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em class="jxr_javadoccomment"> * @since 3.3</em>
+<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em class="jxr_javadoccomment"> */</em>
+<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> <a href="../../../../../../org/apache/commons/math3/stat/inference/KolmogorovSmirnovTestTest.html">KolmogorovSmirnovTestTest</a> {
+<a class="jxr_linenumber" name="L37" href="#L37">37</a>  
+<a class="jxr_linenumber" name="L38" href="#L38">38</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> TOLERANCE = 10e-10;
+<a class="jxr_linenumber" name="L39" href="#L39">39</a>  
+<a class="jxr_linenumber" name="L40" href="#L40">40</a>      <em class="jxr_comment">// Random N(0,1) values generated using R rnorm</em>
+<a class="jxr_linenumber" name="L41" href="#L41">41</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] gaussian = {
+<a class="jxr_linenumber" name="L42" href="#L42">42</a>          0.26055895, -0.63665233, 1.51221323, 0.61246988, -0.03013003, -1.73025682, -0.51435805, 0.70494168, 0.18242945,
+<a class="jxr_linenumber" name="L43" href="#L43">43</a>          0.94734336, -0.04286604, -0.37931719, -1.07026403, -2.05861425, 0.11201862, 0.71400136, -0.52122185,
+<a class="jxr_linenumber" name="L44" href="#L44">44</a>          -0.02478725, -1.86811649, -1.79907688, 0.15046279, 1.32390193, 1.55889719, 1.83149171, -0.03948003,
+<a class="jxr_linenumber" name="L45" href="#L45">45</a>          -0.98579207, -0.76790540, 0.89080682, 0.19532153, 0.40692841, 0.15047336, -0.58546562, -0.39865469, 0.77604271,
+<a class="jxr_linenumber" name="L46" href="#L46">46</a>          -0.65188221, -1.80368554, 0.65273365, -0.75283102, -1.91022150, -0.07640869, -1.08681188, -0.89270600,
+<a class="jxr_linenumber" name="L47" href="#L47">47</a>          2.09017508, 0.43907981, 0.10744033, -0.70961218, 1.15707300, 0.44560525, -2.04593349, 0.53816843, -0.08366640,
+<a class="jxr_linenumber" name="L48" href="#L48">48</a>          0.24652218, 1.80549401, -0.99220707, -1.14589408, -0.27170290, -0.49696855, 0.00968353, -1.87113545,
+<a class="jxr_linenumber" name="L49" href="#L49">49</a>          -1.91116529, 0.97151891, -0.73576115, -0.59437029, 0.72148436, 0.01747695, -0.62601157, -1.00971538,
+<a class="jxr_linenumber" name="L50" href="#L50">50</a>          -1.42691397, 1.03250131, -0.30672627, -0.15353992, -1.19976069, -0.68364218, 0.37525652, -0.46592881,
+<a class="jxr_linenumber" name="L51" href="#L51">51</a>          -0.52116168, -0.17162202, 1.04679215, 0.25165971, -0.04125231, -0.23756244, -0.93389975, 0.75551407,
+<a class="jxr_linenumber" name="L52" href="#L52">52</a>          0.08347445, -0.27482228, -0.4717632, -0.1867746, -0.1166976, 0.5763333, 0.1307952, 0.7630584, -0.3616248,
+<a class="jxr_linenumber" name="L53" href="#L53">53</a>          2.1383790, -0.7946630, 0.0231885, 0.7919195, 1.6057144, -0.3802508, 0.1229078, 1.5252901, -0.8543149, 0.3025040
+<a class="jxr_linenumber" name="L54" href="#L54">54</a>      };
+<a class="jxr_linenumber" name="L55" href="#L55">55</a>  
+<a class="jxr_linenumber" name="L56" href="#L56">56</a>      <em class="jxr_comment">// Random N(0, 1.6) values generated using R rnorm</em>
+<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] gaussian2 = {
+<a class="jxr_linenumber" name="L58" href="#L58">58</a>          2.88041498038308, -0.632349445671017, 0.402121295225571, 0.692626364613243, 1.30693446815426,
+<a class="jxr_linenumber" name="L59" href="#L59">59</a>          -0.714176317131286, -0.233169206599583, 1.09113298322107, -1.53149079994305, 1.23259966205809,
+<a class="jxr_linenumber" name="L60" href="#L60">60</a>          1.01389927412503, 0.0143898711497477, -0.512813545447559, 2.79364360835469, 0.662008875538092,
+<a class="jxr_linenumber" name="L61" href="#L61">61</a>          1.04861546834788, -0.321280099931466, 0.250296656278743, 1.75820367603736, -2.31433523590905,
+<a class="jxr_linenumber" name="L62" href="#L62">62</a>          -0.462694696086403, 0.187725700950191, -2.24410950019152, 2.83473751105445, 0.252460174391016,
+<a class="jxr_linenumber" name="L63" href="#L63">63</a>          1.39051945380281, -1.56270144203134, 0.998522814471644, -1.50147469080896, 0.145307533554146,
+<a class="jxr_linenumber" name="L64" href="#L64">64</a>          0.469089457043406, -0.0914780723809334, -0.123446939266548, -0.610513388160565, -3.71548343891957,
+<a class="jxr_linenumber" name="L65" href="#L65">65</a>          -0.329577317349478, -0.312973794075871, 2.02051909758923, 2.85214308266271, 0.0193222002327237,
+<a class="jxr_linenumber" name="L66" href="#L66">66</a>          -0.0322422268266562, 0.514736012106768, 0.231484953375887, -2.22468798953629, 1.42197716075595,
+<a class="jxr_linenumber" name="L67" href="#L67">67</a>          2.69988043856357, 0.0443757119128293, 0.721536984407798, -0.0445688839903234, -0.294372724550705,
+<a class="jxr_linenumber" name="L68" href="#L68">68</a>          0.234041580912698, -0.868973119365727, 1.3524893453845, -0.931054600134503, -0.263514296006792,
+<a class="jxr_linenumber" name="L69" href="#L69">69</a>          0.540949457402918, -0.882544288773685, -0.34148675747989, 1.56664494810034, 2.19850536566584,
+<a class="jxr_linenumber" name="L70" href="#L70">70</a>          -0.667972122928022, -0.70889669526203, -0.00251758193079668, 2.39527162977682, -2.7559594317269,
+<a class="jxr_linenumber" name="L71" href="#L71">71</a>          -0.547393502656671, -2.62144031572617, 2.81504147017922, -1.02036850201042, -1.00713927602786,
+<a class="jxr_linenumber" name="L72" href="#L72">72</a>          -0.520197775122254, 1.00625480138649, 2.46756916531313, 1.64364743727799, 0.704545210648595,
+<a class="jxr_linenumber" name="L73" href="#L73">73</a>          -0.425885789416992, -1.78387854908546, -0.286783886710481, 0.404183648369076, -0.369324280845769,
+<a class="jxr_linenumber" name="L74" href="#L74">74</a>          -0.0391185138840443, 2.41257787857293, 2.49744281317859, -0.826964496939021, -0.792555379958975,
+<a class="jxr_linenumber" name="L75" href="#L75">75</a>          1.81097685787403, -0.475014580016638, 1.23387615291805, 0.646615294802053, 1.88496377454523, 1.20390698380814,
+<a class="jxr_linenumber" name="L76" href="#L76">76</a>          -0.27812153371728, 2.50149494533101, 0.406964323253817, -1.72253451309982, 1.98432494184332, 2.2223658560333,
+<a class="jxr_linenumber" name="L77" href="#L77">77</a>          0.393086362404685, -0.504073151377089, -0.0484610869883821
+<a class="jxr_linenumber" name="L78" href="#L78">78</a>      };
+<a class="jxr_linenumber" name="L79" href="#L79">79</a>  
+<a class="jxr_linenumber" name="L80" href="#L80">80</a>      <em class="jxr_comment">// Random uniform (0, 1) generated using R runif</em>
+<a class="jxr_linenumber" name="L81" href="#L81">81</a>      <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] uniform = {
+<a class="jxr_linenumber" name="L82" href="#L82">82</a>          0.7930305, 0.6424382, 0.8747699, 0.7156518, 0.1845909, 0.2022326, 0.4877206, 0.8928752, 0.2293062, 0.4222006,
+<a class="jxr_linenumber" name="L83" href="#L83">83</a>          0.1610459, 0.2830535, 0.9946345, 0.7329499, 0.26411126, 0.87958133, 0.29827437, 0.39185988, 0.38351185,
+<a class="jxr_linenumber" name="L84" href="#L84">84</a>          0.36359611, 0.48646472, 0.05577866, 0.56152250, 0.52672013, 0.13171783, 0.95864085, 0.03060207, 0.33514887,
+<a class="jxr_linenumber" name="L85" href="#L85">85</a>          0.72508148, 0.38901437, 0.9978665, 0.5981300, 0.1065388, 0.7036991, 0.1071584, 0.4423963, 0.1107071, 0.6437221,
+<a class="jxr_linenumber" name="L86" href="#L86">86</a>          0.58523872, 0.05044634, 0.65999539, 0.37367260, 0.73270024, 0.47473755, 0.74661163, 0.50765549, 0.05377347,
+<a class="jxr_linenumber" name="L87" href="#L87">87</a>          0.40998009, 0.55235182, 0.21361998, 0.63117971, 0.18109222, 0.89153510, 0.23203248, 0.6177106, 0.6856418,
+<a class="jxr_linenumber" name="L88" href="#L88">88</a>          0.2158557, 0.9870501, 0.2036914, 0.2100311, 0.9065020, 0.7459159, 0.56631790, 0.06753629, 0.39684629,
+<a class="jxr_linenumber" name="L89" href="#L89">89</a>          0.52504615, 0.14199103, 0.78551120, 0.90503321, 0.80452362, 0.9960115, 0.8172592, 0.5831134, 0.8794187,
+<a class="jxr_linenumber" name="L90" href="#L90">90</a>          0.2021501, 0.2923505, 0.9561824, 0.8792248, 0.85201008, 0.02945562, 0.26200374, 0.11382818, 0.17238856,
+<a class="jxr_linenumber" name="L91" href="#L91">91</a>          0.36449473, 0.69688273, 0.96216330, 0.4859432, 0.4503438, 0.1917656, 0.8357845, 0.9957812, 0.4633570,
+<a class="jxr_linenumber" name="L92" href="#L92">92</a>          0.8654599, 0.4597996, 0.68190289, 0.58887855, 0.09359396, 0.98081979, 0.73659533, 0.89344777, 0.18903099,
+<a class="jxr_linenumber" name="L93" href="#L93">93</a>          0.97660425
+<a class="jxr_linenumber" name="L94" href="#L94">94</a>      };
+<a class="jxr_linenumber" name="L95" href="#L95">95</a>  
+<a class="jxr_linenumber" name="L96" href="#L96">96</a>      <em class="jxr_javadoccomment">/** Unit normal distribution, unit normal data */</em>
+<a class="jxr_linenumber" name="L97" href="#L97">97</a>      @Test
+<a class="jxr_linenumber" name="L98" href="#L98">98</a>      <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianGaussian() {
+<a class="jxr_linenumber" name="L99" href="#L99">99</a>          <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L100" href="#L100">100</a>         <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
+<a class="jxr_linenumber" name="L101" href="#L101">101</a>         <em class="jxr_comment">// Uncomment to run exact test - takes about a minute. Same value is used in R tests and for</em>
+<a class="jxr_linenumber" name="L102" href="#L102">102</a>         <em class="jxr_comment">// approx.</em>
+<a class="jxr_linenumber" name="L103" href="#L103">103</a>         <em class="jxr_comment">// Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, gaussian,</em>
+<a class="jxr_linenumber" name="L104" href="#L104">104</a>         <em class="jxr_comment">// true), TOLERANCE);</em>
+<a class="jxr_linenumber" name="L105" href="#L105">105</a>         Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, gaussian, false), TOLERANCE);
+<a class="jxr_linenumber" name="L106" href="#L106">106</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
+<a class="jxr_linenumber" name="L107" href="#L107">107</a>         Assert.assertEquals(0.0932947561266756, test.kolmogorovSmirnovStatistic(unitNormal, gaussian), TOLERANCE);
+<a class="jxr_linenumber" name="L108" href="#L108">108</a>     }
+<a class="jxr_linenumber" name="L109" href="#L109">109</a> 
+<a class="jxr_linenumber" name="L110" href="#L110">110</a>     <em class="jxr_javadoccomment">/** Unit normal distribution, unit normal data, small dataset */</em>
+<a class="jxr_linenumber" name="L111" href="#L111">111</a>     @Test
+<a class="jxr_linenumber" name="L112" href="#L112">112</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianGaussianSmallSample() {
+<a class="jxr_linenumber" name="L113" href="#L113">113</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L114" href="#L114">114</a>         <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
+<a class="jxr_linenumber" name="L115" href="#L115">115</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[50];
+<a class="jxr_linenumber" name="L116" href="#L116">116</a>         System.arraycopy(gaussian, 0, shortGaussian, 0, 50);
+<a class="jxr_linenumber" name="L117" href="#L117">117</a>         Assert.assertEquals(0.683736463728347, test.kolmogorovSmirnovTest(unitNormal, shortGaussian, false), TOLERANCE);
+<a class="jxr_linenumber" name="L118" href="#L118">118</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
+<a class="jxr_linenumber" name="L119" href="#L119">119</a>         Assert.assertEquals(0.09820779969463278, test.kolmogorovSmirnovStatistic(unitNormal, shortGaussian), TOLERANCE);
+<a class="jxr_linenumber" name="L120" href="#L120">120</a>     }
+<a class="jxr_linenumber" name="L121" href="#L121">121</a> 
+<a class="jxr_linenumber" name="L122" href="#L122">122</a>     <em class="jxr_javadoccomment">/** Unit normal distribution, uniform data */</em>
+<a class="jxr_linenumber" name="L123" href="#L123">123</a>     @Test
+<a class="jxr_linenumber" name="L124" href="#L124">124</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleGaussianUniform() {
+<a class="jxr_linenumber" name="L125" href="#L125">125</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L126" href="#L126">126</a>         <strong class="jxr_keyword">final</strong> NormalDistribution unitNormal = <strong class="jxr_keyword">new</strong> NormalDistribution(0d, 1d);
+<a class="jxr_linenumber" name="L127" href="#L127">127</a>         <em class="jxr_comment">// Uncomment to run exact test - takes a long time. Same value is used in R tests and for</em>
+<a class="jxr_linenumber" name="L128" href="#L128">128</a>         <em class="jxr_comment">// approx.</em>
+<a class="jxr_linenumber" name="L129" href="#L129">129</a>         <em class="jxr_comment">// Assert.assertEquals(0.3172069207622391, test.kolmogorovSmirnovTest(unitNormal, uniform,</em>
+<a class="jxr_linenumber" name="L130" href="#L130">130</a>         <em class="jxr_comment">// true), TOLERANCE);</em>
+<a class="jxr_linenumber" name="L131" href="#L131">131</a>         Assert.assertEquals(8.881784197001252E-16, test.kolmogorovSmirnovTest(unitNormal, uniform, false), TOLERANCE);
+<a class="jxr_linenumber" name="L132" href="#L132">132</a>         Assert.assertFalse(test.kolmogorovSmirnovTest(unitNormal, gaussian, 0.05));
+<a class="jxr_linenumber" name="L133" href="#L133">133</a>         Assert.assertEquals(0.5117493931609258, test.kolmogorovSmirnovStatistic(unitNormal, uniform), TOLERANCE);
+<a class="jxr_linenumber" name="L134" href="#L134">134</a>     }
+<a class="jxr_linenumber" name="L135" href="#L135">135</a> 
+<a class="jxr_linenumber" name="L136" href="#L136">136</a>     <em class="jxr_javadoccomment">/** Uniform distribution, uniform data */</em>
+<a class="jxr_linenumber" name="L137" href="#L137">137</a>     <em class="jxr_comment">// @Test - takes about 6 seconds, uncomment for</em>
+<a class="jxr_linenumber" name="L138" href="#L138">138</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformUniform() {
+<a class="jxr_linenumber" name="L139" href="#L139">139</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L140" href="#L140">140</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
+<a class="jxr_linenumber" name="L141" href="#L141">141</a>         Assert.assertEquals(8.881784197001252E-16, test.kolmogorovSmirnovTest(unif, uniform, false), TOLERANCE);
+<a class="jxr_linenumber" name="L142" href="#L142">142</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, uniform, 0.05));
+<a class="jxr_linenumber" name="L143" href="#L143">143</a>         Assert.assertEquals(0.5400666982352942, test.kolmogorovSmirnovStatistic(unif, uniform), TOLERANCE);
+<a class="jxr_linenumber" name="L144" href="#L144">144</a>     }
+<a class="jxr_linenumber" name="L145" href="#L145">145</a> 
+<a class="jxr_linenumber" name="L146" href="#L146">146</a>     <em class="jxr_javadoccomment">/** Uniform distribution, uniform data, small dataset */</em>
+<a class="jxr_linenumber" name="L147" href="#L147">147</a>     @Test
+<a class="jxr_linenumber" name="L148" href="#L148">148</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformUniformSmallSample() {
+<a class="jxr_linenumber" name="L149" href="#L149">149</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L150" href="#L150">150</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
+<a class="jxr_linenumber" name="L151" href="#L151">151</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortUniform = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[20];
+<a class="jxr_linenumber" name="L152" href="#L152">152</a>         System.arraycopy(uniform, 0, shortUniform, 0, 20);
+<a class="jxr_linenumber" name="L153" href="#L153">153</a>         Assert.assertEquals(4.117594598618268E-9, test.kolmogorovSmirnovTest(unif, shortUniform, false), TOLERANCE);
+<a class="jxr_linenumber" name="L154" href="#L154">154</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, shortUniform, 0.05));
+<a class="jxr_linenumber" name="L155" href="#L155">155</a>         Assert.assertEquals(0.6610459, test.kolmogorovSmirnovStatistic(unif, shortUniform), TOLERANCE);
+<a class="jxr_linenumber" name="L156" href="#L156">156</a>     }
+<a class="jxr_linenumber" name="L157" href="#L157">157</a> 
+<a class="jxr_linenumber" name="L158" href="#L158">158</a>     <em class="jxr_javadoccomment">/** Uniform distribution, unit normal dataset */</em>
+<a class="jxr_linenumber" name="L159" href="#L159">159</a>     @Test
+<a class="jxr_linenumber" name="L160" href="#L160">160</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testOneSampleUniformGaussian() {
+<a class="jxr_linenumber" name="L161" href="#L161">161</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L162" href="#L162">162</a>         <strong class="jxr_keyword">final</strong> UniformRealDistribution unif = <strong class="jxr_keyword">new</strong> UniformRealDistribution(-0.5, 0.5);
+<a class="jxr_linenumber" name="L163" href="#L163">163</a>         <em class="jxr_comment">// Value was obtained via exact test, validated against R. Running exact test takes a long</em>
+<a class="jxr_linenumber" name="L164" href="#L164">164</a>         <em class="jxr_comment">// time.</em>
+<a class="jxr_linenumber" name="L165" href="#L165">165</a>         Assert.assertEquals(4.9405812774239166E-11, test.kolmogorovSmirnovTest(unif, gaussian, false), TOLERANCE);
+<a class="jxr_linenumber" name="L166" href="#L166">166</a>         Assert.assertTrue(test.kolmogorovSmirnovTest(unif, gaussian, 0.05));
+<a class="jxr_linenumber" name="L167" href="#L167">167</a>         Assert.assertEquals(0.3401058049019608, test.kolmogorovSmirnovStatistic(unif, gaussian), TOLERANCE);
+<a class="jxr_linenumber" name="L168" href="#L168">168</a>     }
+<a class="jxr_linenumber" name="L169" href="#L169">169</a> 
+<a class="jxr_linenumber" name="L170" href="#L170">170</a>     <em class="jxr_javadoccomment">/** Small samples - exact p-value, checked against R */</em>
+<a class="jxr_linenumber" name="L171" href="#L171">171</a>     @Test
+<a class="jxr_linenumber" name="L172" href="#L172">172</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleSmallSampleExact() {
+<a class="jxr_linenumber" name="L173" href="#L173">173</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L174" href="#L174">174</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] smallSample1 = {
+<a class="jxr_linenumber" name="L175" href="#L175">175</a>             6, 7, 9, 13, 19, 21, 22, 23, 24
+<a class="jxr_linenumber" name="L176" href="#L176">176</a>         };
+<a class="jxr_linenumber" name="L177" href="#L177">177</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] smallSample2 = {
+<a class="jxr_linenumber" name="L178" href="#L178">178</a>             10, 11, 12, 16, 20, 27, 28, 32, 44, 54
+<a class="jxr_linenumber" name="L179" href="#L179">179</a>         };
+<a class="jxr_linenumber" name="L180" href="#L180">180</a>         <em class="jxr_comment">// Reference values from R, version 2.15.3 - R uses non-strict inequality in null hypothesis</em>
+<a class="jxr_linenumber" name="L181" href="#L181">181</a>         Assert
+<a class="jxr_linenumber" name="L182" href="#L182">182</a>             .assertEquals(0.105577085453247, test.kolmogorovSmirnovTest(smallSample1, smallSample2, false), TOLERANCE);
+<a class="jxr_linenumber" name="L183" href="#L183">183</a>         Assert.assertEquals(0.5, test.kolmogorovSmirnovStatistic(smallSample1, smallSample2), TOLERANCE);
+<a class="jxr_linenumber" name="L184" href="#L184">184</a>     }
+<a class="jxr_linenumber" name="L185" href="#L185">185</a> 
+<a class="jxr_linenumber" name="L186" href="#L186">186</a>     <em class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L187" href="#L187">187</a> <em class="jxr_javadoccomment">     * Checks exact p-value computations using critical values from Table 9 in V.K Rohatgi, An</em>
+<a class="jxr_linenumber" name="L188" href="#L188">188</a> <em class="jxr_javadoccomment">     * Introduction to Probability and Mathematical Statistics, Wiley, 1976, ISBN 0-471-73135-8.</em>
+<a class="jxr_linenumber" name="L189" href="#L189">189</a> <em class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L190" href="#L190">190</a>     @Test
+<a class="jxr_linenumber" name="L191" href="#L191">191</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleExactP() {
+<a class="jxr_linenumber" name="L192" href="#L192">192</a>         checkExactTable(4, 6, 5d / 6d, 0.01d);
+<a class="jxr_linenumber" name="L193" href="#L193">193</a>         checkExactTable(4, 7, 17d / 28d, 0.2d);
+<a class="jxr_linenumber" name="L194" href="#L194">194</a>         checkExactTable(6, 7, 29d / 42d, 0.05d);
+<a class="jxr_linenumber" name="L195" href="#L195">195</a>         checkExactTable(4, 10, 7d / 10d, 0.05d);
+<a class="jxr_linenumber" name="L196" href="#L196">196</a>         checkExactTable(5, 15, 11d / 15d, 0.02d);
+<a class="jxr_linenumber" name="L197" href="#L197">197</a>         checkExactTable(9, 10, 31d / 45d, 0.01d);
+<a class="jxr_linenumber" name="L198" href="#L198">198</a>         checkExactTable(7, 10, 43d / 70d, 0.05d);
+<a class="jxr_linenumber" name="L199" href="#L199">199</a>     }
+<a class="jxr_linenumber" name="L200" href="#L200">200</a> 
+<a class="jxr_linenumber" name="L201" href="#L201">201</a>     @Test
+<a class="jxr_linenumber" name="L202" href="#L202">202</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleApproximateCritialValues() {
+<a class="jxr_linenumber" name="L203" href="#L203">203</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = .01;
+<a class="jxr_linenumber" name="L204" href="#L204">204</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] alpha = {
+<a class="jxr_linenumber" name="L205" href="#L205">205</a>             0.10, 0.05, 0.025, 0.01, 0.005, 0.001
 <a class="jxr_linenumber" name="L206" href="#L206">206</a>         };
-<a class="jxr_linenumber" name="L207" href="#L207">207</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> k[] = {
-<a class="jxr_linenumber" name="L208" href="#L208">208</a>             60, 100, 500
-<a class="jxr_linenumber" name="L209" href="#L209">209</a>         };
-<a class="jxr_linenumber" name="L210" href="#L210">210</a>         <strong class="jxr_keyword">double</strong> n;
-<a class="jxr_linenumber" name="L211" href="#L211">211</a>         <strong class="jxr_keyword">double</strong> m;
-<a class="jxr_linenumber" name="L212" href="#L212">212</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i &lt; k.length; i++) {
-<a class="jxr_linenumber" name="L213" href="#L213">213</a>             <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> j = 0; j &lt; i; j++) {
-<a class="jxr_linenumber" name="L214" href="#L214">214</a>                 n = k[i];
-<a class="jxr_linenumber" name="L215" href="#L215">215</a>                 m = k[j];
-<a class="jxr_linenumber" name="L216" href="#L216">216</a>                 <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> l = 0; l &lt; alpha.length; l++) {
-<a class="jxr_linenumber" name="L217" href="#L217">217</a>                     <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> dCrit = c[l] * FastMath.sqrt((n + m) / (n * m));
-<a class="jxr_linenumber" name="L218" href="#L218">218</a>                     checkApproximateTable(k[i], k[j], dCrit, alpha[l], tol);
-<a class="jxr_linenumber" name="L219" href="#L219">219</a>                 }
-<a class="jxr_linenumber" name="L220" href="#L220">220</a>             }
-<a class="jxr_linenumber" name="L221" href="#L221">221</a>         }
-<a class="jxr_linenumber" name="L222" href="#L222">222</a>     }
-<a class="jxr_linenumber" name="L223" href="#L223">223</a> 
-<a class="jxr_linenumber" name="L224" href="#L224">224</a>     @Test
-<a class="jxr_linenumber" name="L225" href="#L225">225</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testPelzGoodApproximation() {
-<a class="jxr_linenumber" name="L226" href="#L226">226</a>         KolmogorovSmirnovTest ksTest = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L227" href="#L227">227</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> d[] = {0.15, 0.20, 0.25, 0.3, 0.35, 0.4};
-<a class="jxr_linenumber" name="L228" href="#L228">228</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> n[] = {141, 150, 180, 220, 1000};
-<a class="jxr_linenumber" name="L229" href="#L229">229</a>         <em class="jxr_comment">// Reference values computed using the Pelz method from</em>
-<a class="jxr_linenumber" name="L230" href="#L230">230</a>         <em class="jxr_comment">// http://simul.iro.umontreal.ca/ksdir/KolmogorovSmirnovDist.java</em>
-<a class="jxr_linenumber" name="L231" href="#L231">231</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> ref[] = {
-<a class="jxr_linenumber" name="L232" href="#L232">232</a>             0.9968940168727819, 0.9979326624184857, 0.9994677598604506, 0.9999128354780209, 0.9999999999998661,
-<a class="jxr_linenumber" name="L233" href="#L233">233</a>             0.9999797514476236, 0.9999902122242081, 0.9999991327060908, 0.9999999657681911, 0.9999999999977929,
-<a class="jxr_linenumber" name="L234" href="#L234">234</a>             0.9999999706444976, 0.9999999906571532, 0.9999999997949596, 0.999999999998745, 0.9999999999993876,
-<a class="jxr_linenumber" name="L235" href="#L235">235</a>             0.9999999999916627, 0.9999999999984447, 0.9999999999999936, 0.999999999999341, 0.9999999999971508,
-<a class="jxr_linenumber" name="L236" href="#L236">236</a>             0.9999999999999877, 0.9999999999999191, 0.9999999999999254, 0.9999999999998178, 0.9999999999917788,
-<a class="jxr_linenumber" name="L237" href="#L237">237</a>             0.9999999999998556, 0.9999999999992014, 0.9999999999988859, 0.9999999999999325, 0.9999999999821726
-<a class="jxr_linenumber" name="L238" href="#L238">238</a>         };
-<a class="jxr_linenumber" name="L239" href="#L239">239</a> 
-<a class="jxr_linenumber" name="L240" href="#L240">240</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = 10e-15;
-<a class="jxr_linenumber" name="L241" href="#L241">241</a>         <strong class="jxr_keyword">int</strong> k = 0;
-<a class="jxr_linenumber" name="L242" href="#L242">242</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i &lt; 6; i++) {
-<a class="jxr_linenumber" name="L243" href="#L243">243</a>             <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> j = 0; j &lt; 5; j++, k++) {
-<a class="jxr_linenumber" name="L244" href="#L244">244</a>                 Assert.assertEquals(ref[k], ksTest.pelzGood(d[i], n[j]), tol);
-<a class="jxr_linenumber" name="L245" href="#L245">245</a>             }
-<a class="jxr_linenumber" name="L246" href="#L246">246</a>         }
-<a class="jxr_linenumber" name="L247" href="#L247">247</a>     }
-<a class="jxr_linenumber" name="L248" href="#L248">248</a> 
-<a class="jxr_linenumber" name="L249" href="#L249">249</a>     <em class="jxr_javadoccomment">/** Verifies large sample approximate p values against R */</em>
-<a class="jxr_linenumber" name="L250" href="#L250">250</a>     @Test
-<a class="jxr_linenumber" name="L251" href="#L251">251</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleApproximateP() {
-<a class="jxr_linenumber" name="L252" href="#L252">252</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L253" href="#L253">253</a>         <em class="jxr_comment">// Reference values from R, version 2.15.3</em>
-<a class="jxr_linenumber" name="L254" href="#L254">254</a>         Assert.assertEquals(0.0319983962391632, test.kolmogorovSmirnovTest(gaussian, gaussian2), TOLERANCE);
-<a class="jxr_linenumber" name="L255" href="#L255">255</a>         Assert.assertEquals(0.202352941176471, test.kolmogorovSmirnovStatistic(gaussian, gaussian2), TOLERANCE);
-<a class="jxr_linenumber" name="L256" href="#L256">256</a>     }
-<a class="jxr_linenumber" name="L257" href="#L257">257</a> 
-<a class="jxr_linenumber" name="L258" href="#L258">258</a>     <em class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L259" href="#L259">259</a> <em class="jxr_javadoccomment">     * MATH-1181</em>
-<a class="jxr_linenumber" name="L260" href="#L260">260</a> <em class="jxr_javadoccomment">     * Verify that large sample method is selected for sample product &gt; Integer.MAX_VALUE</em>
-<a class="jxr_linenumber" name="L261" href="#L261">261</a> <em class="jxr_javadoccomment">     * (integer overflow in sample product)</em>
-<a class="jxr_linenumber" name="L262" href="#L262">262</a> <em class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L263" href="#L263">263</a>     @Test(timeout=5000)
-<a class="jxr_linenumber" name="L264" href="#L264">264</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleProductSizeOverflow() {
-<a class="jxr_linenumber" name="L265" href="#L265">265</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> n = 50000;
-<a class="jxr_linenumber" name="L266" href="#L266">266</a>         Assert.assertTrue(n * n &lt; 0);
-<a class="jxr_linenumber" name="L267" href="#L267">267</a>         <strong class="jxr_keyword">double</strong>[] x = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[n];
-<a class="jxr_linenumber" name="L268" href="#L268">268</a>         <strong class="jxr_keyword">double</strong>[] y = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[n];
-<a class="jxr_linenumber" name="L269" href="#L269">269</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
-<a class="jxr_linenumber" name="L270" href="#L270">270</a>         Assert.assertFalse(Double.isNaN(test.kolmogorovSmirnovTest(x, y)));
-<a class="jxr_linenumber" name="L271" href="#L271">271</a>     }
-<a class="jxr_linenumber" name="L272" href="#L272">272</a> 
-<a class="jxr_linenumber" name="L273" href="#L273">273</a> 
-<a class="jxr_linenumber" name="L274" href="#L274">274</a>     <em class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L275" href="#L275">275</a> <em class="jxr_javadoccomment">     * Verifies that Monte Carlo simulation gives results close to exact p values. This test is a</em>
-<a class="jxr_linenumber" name="L276" href="#L276">276</a> <em class="jxr_javadoccomment">     * little long-running (more than two minutes on a fast machine), so is disabled by default.</em>
-<a class="jxr_linenumber" name="L277" href="#L277">277</a> <em class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L278" href="#L278">278</a>     <em class="jxr_comment">// @Test</em>
-<a class="jxr_linenumber" name="L279" href="#L279">279</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleMonteCarlo() {
-<a class="jxr_linenumber" name="L280" href="#L280">280</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest(<strong class="jxr_keyword">new</strong> Well19937c(1000));
-<a class="jxr_linenumber" name="L281" href="#L281">281</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> sampleSize = 14;
-<a class="jxr_linenumber" name="L282" href="#L282">282</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = .001;
-<a class="jxr_linenumber" name="L283" href="#L283">283</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortUniform = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
-<a class="jxr_linenumber" name="L284" href="#L284">284</a>         System.arraycopy(uniform, 0, shortUniform, 0, sampleSize);
-<a class="jxr_linenumber" name="L285" href="#L285">285</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
-<a class="jxr_linenumber" name="L286" href="#L286">286</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian2 = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
-<a class="jxr_linenumber" name="L287" href="#L287">287</a>         System.arraycopy(gaussian, 0, shortGaussian, 0, sampleSize);
-<a class="jxr_linenumber" name="L288" href="#L288">288</a>         System.arraycopy(gaussian, 10, shortGaussian2, 0, sampleSize);
-<a class="jxr_linenumber" name="L289" href="#L289">289</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] d = {
-<a class="jxr_linenumber" name="L290" href="#L290">290</a>             test.kolmogorovSmirnovStatistic(shortGaussian, shortUniform),
-<a class="jxr_linenumber" name="L291" href="#L291">291</a>             test.kolmogorovSmirnovStatistic(shortGaussian2, shortGaussian)
-<a class="jxr_linenumber" name="L292" href="#L292">292</a>         };
-<a class="jxr_linenumber" name="L293" href="#L293">293</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">double</strong> dv : d) {
-<a class="jxr_linenumber" name="L294" href="#L294">294</a>             <strong class="jxr_keyword">double</strong> exactPStrict = test.exactP(dv, sampleSize, sampleSize, <strong class="jxr_keyword">true</strong>);
-<a class="jxr_linenumber" name="L295" href="#L295">295</a>             <strong class="jxr_keyword">double</strong> exactPNonStrict = test.exactP(dv, sampleSize, sampleSize, false);
-<a class="jxr_linenumber" name="L296" href="#L296">296</a>             <strong class="jxr_keyword">double</strong> montePStrict = test.monteCarloP(dv, sampleSize, sampleSize, <strong class="jxr_keyword">true</strong>,
-<a class="jxr_linenumber" name="L297" href="#L297">297</a>                                                    KolmogorovSmirnovTest.MONTE_CARLO_ITERATIONS);
-<a class="jxr_linenumber" name="L298" href="#L298">298</a>             <strong class="jxr_keyword">double</strong> montePNonStrict = test.monteCarloP(dv, sampleSize, sampleSize, false,
-<a class="jxr_linenumber" name="L299" href="#L299">299</a>                                                       KolmogorovSmirnovTest.MONTE_CARLO_ITERATIONS);
-<a class="jxr_linenumber" name="L300" href="#L300">300</a>             Assert.assertEquals(exactPStrict, montePStrict, tol);
-<a class="jxr_linenumber" name="L301" href="#L301">301</a>             Assert.assertEquals(exactPNonStrict, montePNonStrict, tol);
-<a class="jxr_linenumber" name="L302" href="#L302">302</a>         }
-<a class="jxr_linenumber" name="L303" href="#L303">303</a>     }
-<a class="jxr_linenumber" name="L304" href="#L304">304</a> 
-<a class="jxr_linenumber" name="L305" href="#L305">305</a>     @Test
-<a class="jxr_linenumber" name="L306" href="#L306">306</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleWithManyTies() {
-<a class="jxr_linenumber" name="L307" href="#L307">307</a>         <em class="jxr_comment">// MATH-1197</em>
-<a class="jxr_linenumber" name="L308" href="#L308">308</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] x = {
-<a class="jxr_linenumber" name="L309" href="#L309">309</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L310" href="#L310">310</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L311" href="#L311">311</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L312" href="#L312">312</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L313" href="#L313">313</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L314" href="#L314">314</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L315" href="#L315">315</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L316" href="#L316">316</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L317" href="#L317">317</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L318" href="#L318">318</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L319" href="#L319">319</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L320" href="#L320">320</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L321" href="#L321">321</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L322" href="#L322">322</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L323" href="#L323">323</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L324" href="#L324">324</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L325" href="#L325">325</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L326" href="#L326">326</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L327" href="#L327">327</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L328" href="#L328">328</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L329" href="#L329">329</a>             0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
-<a class="jxr_linenumber" name="L330" href="#L330">330</a>             0.000000, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L331" href="#L331">331</a>             2.202653, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L332" href="#L332">332</a>             2.202653, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L333" href="#L333">333</a>             2.202653, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L334" href="#L334">334</a>             2.202653, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L335" href="#L335">335</a>             2.202653, 2.202653, 2.202653, 2.202653, 2.202653, 2.202653,
-<a class="jxr_linenumber" name="L336" href="#L336">336</a>             3.181199, 3.181199, 3.181199, 3.181199, 3.181199, 3.181199,
-<a class="jxr_linenumber" name="L337" href="#L337">337</a>             3.723539, 3.723539, 3.723539, 3.723539, 4.383482, 4.383482,
-<a class="jxr_linenumber" name="L338" href="#L338">338</a>             4.383482, 4.383482, 5.320671, 5.320671, 5.320671, 5.717284,
-<a class="jxr_linenumber" name="L339" href="#L339">339</a>             6.964001, 7.352165, 8.710510, 8.710510, 8.710510, 8.710510,
-<a class="jxr_linenumber" name="L340" href="#L340">340</a>             8.710510, 8.710510, 9.539004, 9.539004, 10.720619, 17.726077,
-<a class="jxr_linenumber" name="L341" href="#L341">341</a>             17.726077, 17.726077, 17.726077, 22.053875, 23.799144, 27.355308,
-<a class="jxr_linenumber" name="L342" href="#L342">342</a>             30.584960, 30.584960, 30.584960, 30.584960, 30.751808
-<a class="jxr_linenumber" name="L343" href="#L343">343</a>         };
-<a class="jxr_linenumber" name="L344" href="#L344">344</a> 
-<a class="jxr_linenumber" name="L345" href="#L345">345</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] y = {
+<a class="jxr_linenumber" name="L207" href="#L207">207</a>         <em class="jxr_comment">// From Wikipedia KS article - TODO: get (and test) more precise values</em>
+<a class="jxr_linenumber" name="L208" href="#L208">208</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] c = {
+<a class="jxr_linenumber" name="L209" href="#L209">209</a>             1.22, 1.36, 1.48, 1.63, 1.73, 1.95
+<a class="jxr_linenumber" name="L210" href="#L210">210</a>         };
+<a class="jxr_linenumber" name="L211" href="#L211">211</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> k[] = {
+<a class="jxr_linenumber" name="L212" href="#L212">212</a>             60, 100, 500
+<a class="jxr_linenumber" name="L213" href="#L213">213</a>         };
+<a class="jxr_linenumber" name="L214" href="#L214">214</a>         <strong class="jxr_keyword">double</strong> n;
+<a class="jxr_linenumber" name="L215" href="#L215">215</a>         <strong class="jxr_keyword">double</strong> m;
+<a class="jxr_linenumber" name="L216" href="#L216">216</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i &lt; k.length; i++) {
+<a class="jxr_linenumber" name="L217" href="#L217">217</a>             <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> j = 0; j &lt; i; j++) {
+<a class="jxr_linenumber" name="L218" href="#L218">218</a>                 n = k[i];
+<a class="jxr_linenumber" name="L219" href="#L219">219</a>                 m = k[j];
+<a class="jxr_linenumber" name="L220" href="#L220">220</a>                 <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> l = 0; l &lt; alpha.length; l++) {
+<a class="jxr_linenumber" name="L221" href="#L221">221</a>                     <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> dCrit = c[l] * FastMath.sqrt((n + m) / (n * m));
+<a class="jxr_linenumber" name="L222" href="#L222">222</a>                     checkApproximateTable(k[i], k[j], dCrit, alpha[l], tol);
+<a class="jxr_linenumber" name="L223" href="#L223">223</a>                 }
+<a class="jxr_linenumber" name="L224" href="#L224">224</a>             }
+<a class="jxr_linenumber" name="L225" href="#L225">225</a>         }
+<a class="jxr_linenumber" name="L226" href="#L226">226</a>     }
+<a class="jxr_linenumber" name="L227" href="#L227">227</a> 
+<a class="jxr_linenumber" name="L228" href="#L228">228</a>     @Test
+<a class="jxr_linenumber" name="L229" href="#L229">229</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testPelzGoodApproximation() {
+<a class="jxr_linenumber" name="L230" href="#L230">230</a>         KolmogorovSmirnovTest ksTest = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L231" href="#L231">231</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> d[] = {0.15, 0.20, 0.25, 0.3, 0.35, 0.4};
+<a class="jxr_linenumber" name="L232" href="#L232">232</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> n[] = {141, 150, 180, 220, 1000};
+<a class="jxr_linenumber" name="L233" href="#L233">233</a>         <em class="jxr_comment">// Reference values computed using the Pelz method from</em>
+<a class="jxr_linenumber" name="L234" href="#L234">234</a>         <em class="jxr_comment">// http://simul.iro.umontreal.ca/ksdir/KolmogorovSmirnovDist.java</em>
+<a class="jxr_linenumber" name="L235" href="#L235">235</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> ref[] = {
+<a class="jxr_linenumber" name="L236" href="#L236">236</a>             0.9968940168727819, 0.9979326624184857, 0.9994677598604506, 0.9999128354780209, 0.9999999999998661,
+<a class="jxr_linenumber" name="L237" href="#L237">237</a>             0.9999797514476236, 0.9999902122242081, 0.9999991327060908, 0.9999999657681911, 0.9999999999977929,
+<a class="jxr_linenumber" name="L238" href="#L238">238</a>             0.9999999706444976, 0.9999999906571532, 0.9999999997949596, 0.999999999998745, 0.9999999999993876,
+<a class="jxr_linenumber" name="L239" href="#L239">239</a>             0.9999999999916627, 0.9999999999984447, 0.9999999999999936, 0.999999999999341, 0.9999999999971508,
+<a class="jxr_linenumber" name="L240" href="#L240">240</a>             0.9999999999999877, 0.9999999999999191, 0.9999999999999254, 0.9999999999998178, 0.9999999999917788,
+<a class="jxr_linenumber" name="L241" href="#L241">241</a>             0.9999999999998556, 0.9999999999992014, 0.9999999999988859, 0.9999999999999325, 0.9999999999821726
+<a class="jxr_linenumber" name="L242" href="#L242">242</a>         };
+<a class="jxr_linenumber" name="L243" href="#L243">243</a> 
+<a class="jxr_linenumber" name="L244" href="#L244">244</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = 10e-15;
+<a class="jxr_linenumber" name="L245" href="#L245">245</a>         <strong class="jxr_keyword">int</strong> k = 0;
+<a class="jxr_linenumber" name="L246" href="#L246">246</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i &lt; 6; i++) {
+<a class="jxr_linenumber" name="L247" href="#L247">247</a>             <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> j = 0; j &lt; 5; j++, k++) {
+<a class="jxr_linenumber" name="L248" href="#L248">248</a>                 Assert.assertEquals(ref[k], ksTest.pelzGood(d[i], n[j]), tol);
+<a class="jxr_linenumber" name="L249" href="#L249">249</a>             }
+<a class="jxr_linenumber" name="L250" href="#L250">250</a>         }
+<a class="jxr_linenumber" name="L251" href="#L251">251</a>     }
+<a class="jxr_linenumber" name="L252" href="#L252">252</a> 
+<a class="jxr_linenumber" name="L253" href="#L253">253</a>     <em class="jxr_javadoccomment">/** Verifies large sample approximate p values against R */</em>
+<a class="jxr_linenumber" name="L254" href="#L254">254</a>     @Test
+<a class="jxr_linenumber" name="L255" href="#L255">255</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleApproximateP() {
+<a class="jxr_linenumber" name="L256" href="#L256">256</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L257" href="#L257">257</a>         <em class="jxr_comment">// Reference values from R, version 2.15.3</em>
+<a class="jxr_linenumber" name="L258" href="#L258">258</a>         Assert.assertEquals(0.0319983962391632, test.kolmogorovSmirnovTest(gaussian, gaussian2), TOLERANCE);
+<a class="jxr_linenumber" name="L259" href="#L259">259</a>         Assert.assertEquals(0.202352941176471, test.kolmogorovSmirnovStatistic(gaussian, gaussian2), TOLERANCE);
+<a class="jxr_linenumber" name="L260" href="#L260">260</a>     }
+<a class="jxr_linenumber" name="L261" href="#L261">261</a> 
+<a class="jxr_linenumber" name="L262" href="#L262">262</a>     <em class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L263" href="#L263">263</a> <em class="jxr_javadoccomment">     * MATH-1181</em>
+<a class="jxr_linenumber" name="L264" href="#L264">264</a> <em class="jxr_javadoccomment">     * Verify that large sample method is selected for sample product &gt; Integer.MAX_VALUE</em>
+<a class="jxr_linenumber" name="L265" href="#L265">265</a> <em class="jxr_javadoccomment">     * (integer overflow in sample product)</em>
+<a class="jxr_linenumber" name="L266" href="#L266">266</a> <em class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L267" href="#L267">267</a>     @Test(timeout=5000)
+<a class="jxr_linenumber" name="L268" href="#L268">268</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleProductSizeOverflow() {
+<a class="jxr_linenumber" name="L269" href="#L269">269</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> n = 50000;
+<a class="jxr_linenumber" name="L270" href="#L270">270</a>         Assert.assertTrue(n * n &lt; 0);
+<a class="jxr_linenumber" name="L271" href="#L271">271</a>         <strong class="jxr_keyword">double</strong>[] x = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[n];
+<a class="jxr_linenumber" name="L272" href="#L272">272</a>         <strong class="jxr_keyword">double</strong>[] y = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[n];
+<a class="jxr_linenumber" name="L273" href="#L273">273</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest();
+<a class="jxr_linenumber" name="L274" href="#L274">274</a>         Assert.assertFalse(Double.isNaN(test.kolmogorovSmirnovTest(x, y)));
+<a class="jxr_linenumber" name="L275" href="#L275">275</a>     }
+<a class="jxr_linenumber" name="L276" href="#L276">276</a> 
+<a class="jxr_linenumber" name="L277" href="#L277">277</a> 
+<a class="jxr_linenumber" name="L278" href="#L278">278</a>     <em class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L279" href="#L279">279</a> <em class="jxr_javadoccomment">     * Verifies that Monte Carlo simulation gives results close to exact p values. This test is a</em>
+<a class="jxr_linenumber" name="L280" href="#L280">280</a> <em class="jxr_javadoccomment">     * little long-running (more than two minutes on a fast machine), so is disabled by default.</em>
+<a class="jxr_linenumber" name="L281" href="#L281">281</a> <em class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L282" href="#L282">282</a>     <em class="jxr_comment">// @Test</em>
+<a class="jxr_linenumber" name="L283" href="#L283">283</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleMonteCarlo() {
+<a class="jxr_linenumber" name="L284" href="#L284">284</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest(<strong class="jxr_keyword">new</strong> Well19937c(1000));
+<a class="jxr_linenumber" name="L285" href="#L285">285</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> sampleSize = 14;
+<a class="jxr_linenumber" name="L286" href="#L286">286</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = .001;
+<a class="jxr_linenumber" name="L287" href="#L287">287</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortUniform = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
+<a class="jxr_linenumber" name="L288" href="#L288">288</a>         System.arraycopy(uniform, 0, shortUniform, 0, sampleSize);
+<a class="jxr_linenumber" name="L289" href="#L289">289</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
+<a class="jxr_linenumber" name="L290" href="#L290">290</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] shortGaussian2 = <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[sampleSize];
+<a class="jxr_linenumber" name="L291" href="#L291">291</a>         System.arraycopy(gaussian, 0, shortGaussian, 0, sampleSize);
+<a class="jxr_linenumber" name="L292" href="#L292">292</a>         System.arraycopy(gaussian, 10, shortGaussian2, 0, sampleSize);
+<a class="jxr_linenumber" name="L293" href="#L293">293</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] d = {
+<a class="jxr_linenumber" name="L294" href="#L294">294</a>             test.kolmogorovSmirnovStatistic(shortGaussian, shortUniform),
+<a class="jxr_linenumber" name="L295" href="#L295">295</a>             test.kolmogorovSmirnovStatistic(shortGaussian2, shortGaussian)
+<a class="jxr_linenumber" name="L296" href="#L296">296</a>         };
+<a class="jxr_linenumber" name="L297" href="#L297">297</a>         <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">double</strong> dv : d) {
+<a class="jxr_linenumber" name="L298" href="#L298">298</a>             <strong class="jxr_keyword">double</strong> exactPStrict = test.exactP(dv, sampleSize, sampleSize, <strong class="jxr_keyword">true</strong>);
+<a class="jxr_linenumber" name="L299" href="#L299">299</a>             <strong class="jxr_keyword">double</strong> exactPNonStrict = test.exactP(dv, sampleSize, sampleSize, false);
+<a class="jxr_linenumber" name="L300" href="#L300">300</a>             <strong class="jxr_keyword">double</strong> montePStrict = test.monteCarloP(dv, sampleSize, sampleSize, <strong class="jxr_keyword">true</strong>,
+<a class="jxr_linenumber" name="L301" href="#L301">301</a>                                                    KolmogorovSmirnovTest.MONTE_CARLO_ITERATIONS);
+<a class="jxr_linenumber" name="L302" href="#L302">302</a>             <strong class="jxr_keyword">double</strong> montePNonStrict = test.monteCarloP(dv, sampleSize, sampleSize, false,
+<a class="jxr_linenumber" name="L303" href="#L303">303</a>                                                       KolmogorovSmirnovTest.MONTE_CARLO_ITERATIONS);
+<a class="jxr_linenumber" name="L304" href="#L304">304</a>             Assert.assertEquals(exactPStrict, montePStrict, tol);
+<a class="jxr_linenumber" name="L305" href="#L305">305</a>             Assert.assertEquals(exactPNonStrict, montePNonStrict, tol);
+<a class="jxr_linenumber" name="L306" href="#L306">306</a>         }
+<a class="jxr_linenumber" name="L307" href="#L307">307</a>     }
+<a class="jxr_linenumber" name="L308" href="#L308">308</a> 
+<a class="jxr_linenumber" name="L309" href="#L309">309</a>     @Test
+<a class="jxr_linenumber" name="L310" href="#L310">310</a>     <strong class="jxr_keyword">public</strong> <strong class="jxr_keyword">void</strong> testTwoSampleMonteCarloDifferentSampleSizes() {
+<a class="jxr_linenumber" name="L311" href="#L311">311</a>         <strong class="jxr_keyword">final</strong> KolmogorovSmirnovTest test = <strong class="jxr_keyword">new</strong> KolmogorovSmirnovTest(<strong class="jxr_keyword">new</strong> Well19937c(1000));
+<a class="jxr_linenumber" name="L312" href="#L312">312</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> sampleSize1 = 14;
+<a class="jxr_linenumber" name="L313" href="#L313">313</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">int</strong> sampleSize2 = 7;
+<a class="jxr_linenumber" name="L314" href="#L314">314</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> d = 0.3;
+<a class="jxr_linenumber" name="L315" href="#L315">315</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">boolean</strong> strict = false;
+<a class="jxr_linenumber" name="L316" href="#L316">316</a>         <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> tol = 1e-2;
+<a class="jxr_linenumber" name="L317" href="#L317">317</a>         Assert.assertEquals(test.exactP(d, sampleSize1, sampleSize2, strict),
+<a class="jxr_linenumber" name="L318" href="#L318">318</a>                             test.monteCarloP(d, sampleSize1, sampleSize2, strict,
+<a class="jxr_linenumber" name="L319" href="#L319">319</a>                                              KolmogorovSmirnovTest.MONTE_CARLO_ITERATIONS),
+<a class="jxr_linenumber" name="L320" href="#L320">320</a>                             tol);
+<a class="jxr_linenumber" name="L321" href="#L321">321</a>     }

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