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From "Roman Werpachowski (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MATH-359) Normal Distribution implementation gives false cumulative probabilities
Date Fri, 02 Apr 2010 11:22:28 GMT

    [ https://issues.apache.org/jira/browse/MATH-359?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12852790#action_12852790
] 

Roman Werpachowski commented on MATH-359:
-----------------------------------------

The problem arises from the way Normal Gaussian CDF is computed in ACM: via an iterative computation
of the Gamma function. It is better, I think, to use a specialized approximation for the Normal
Gaussian CDF, such as (highly accurate) http://www.netlib.org/specfun/erf. I checked that
for the arguments given it simply returns 1.

> Normal Distribution implementation gives false cumulative probabilities
> -----------------------------------------------------------------------
>
>                 Key: MATH-359
>                 URL: https://issues.apache.org/jira/browse/MATH-359
>             Project: Commons Math
>          Issue Type: Bug
>         Environment: Ubuntu Linux
>            Reporter: Joris
>            Priority: Minor
>
> Package: org.apache.commons.math.distribution
> Class: NormalDistributionImpl
> For a given mean and standard deviation, the class NormalDistributionImpl implements
a normal distribution. Per definition, the function cumulativeProbability(double x) should
return a value on the interval <0,1> (0 and 1 excluded), for any real value of x. However,
the following test case shows that the method cumulativeProbability(double x) gives for some
values wrong results:
> NormalDistributionImpl ncdf=new NormalDistributionImpl(0.06848215242239623,0.21287763557454142);
> try{
> 	System.out.println("Test: "+ncdf.cumulativeProbability(2.636630902183101));
> }catch(MathException e){ System.out.println("Exception has occurred: "+e);}
> Result:
> Test: 1.0000000000000064
> Only in the case where x=Double.POSITIVE_INFINITY,  cumulativeProbability(double x) should
return 1. For all other values of x, the result should be <1.
> The weird result from the above test case is quite likely caused by the data type double.
The 2 most straight forward ways to fix this behavior:
> 1. Use a more accurate data type
> 2. Build in checks which prevent bad results like:
> if(x==Double.POSITIVE_INFINITY)
>    return 1;
> else if(x==Double.NEGATIVE_INFINITY)
>    return 0;
> else if(result >=1)
>    return 0.9999999999999; //A constant value which is stored correctly by a double
> else if(result <=0)
>    return 0.0000000000001;
> Nevertheless, I believe that this issue should be noted in the Javadoc of the NormalDistributionImpl
class. 

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