The Commons Math User Guide

This is yet to be written. Any contributions will be greatfully - accepted!

+ The statistics and distributions packages provide frameworks and implementations for + basic univariate statistics, frequency distributions, bivariate regression, t- and chi-square test + statistics and some commonly used probability distributions. +

This is yet to be written. Any contributions will be gratefully - accepted!

+ The stat package includes a framework and default implementations for the following univariate + statistics: +

arithmetic and geometric means
variance and standard deviation
sum, product, log sum, sum of squared values
minimum, maximum, median, and percentiles
skewness and kurtosis
first, second, third and fourth moments

+ With the exception of percentiles and the median, all of these statistics can be computed without + maintaining the full list of input data values in memory. The stat package provides interfaces and + implementations that do not require value storage as well as implementations that operate on arrays + of stored values. +

+ The top level interface is + + org.apache.commons.math.stat.univariate.UnivariateStatistic. This interface, implemented by + all statistics, consists of evaluate() methods that take double[] arrays as arguments and return + the value of the statistic. This interface is extended by + + org.apache.commons.math.stat.univariate.StorelessUnivariateStatistic, which adds increment(), + getResult() and associated methods to support "storageless" implementations that + maintain counters, sums or other state information as values are added using the increment() + method. +

+ Abstract implementations of the top level interfaces are provided in + + org.apache.commons.math.stat.univariate.AbstractUnivariateStatistic and + + org.apache.commons.math.stat.univariate.AbstractStorelessUnivariateStatistic respectively. +

+ Each statistic is implemented as a separate class, in one of the subpackages (moment, rank, summary) and + each extends one of the abstract classes above (depending on whether or not value storage is required to + compute the statistic). + There are several ways to instantiate and use statistics. Statistics can be instantiated and used directly, but it is + generally more convenient to access them using the provided aggregates: + + + + +
Aggregate Statistics Included Values stored?
+ org.apache.commons.math.stat.DescriptiveStatistics All Yes
+ org.apache.commons.math.stat.SummaryStatistics min, max, mean, geometric mean, n, sum, sum of squares, standard deviation, variance No
+ TODO: add code sample + There is also a utility class, + org.apache.commons.math.stat.StatUtils, that provides static methods for computing statistics + from double[] arrays. +

Aggregate	Statistics Included	Values stored?
+ org.apache.commons.math.stat.DescriptiveStatistics	All	Yes
+ org.apache.commons.math.stat.SummaryStatistics	min, max, mean, geometric mean, n, sum, sum of squares, standard deviation, variance	No

This is yet to be written. Any contributions will be gratefully @@ -73,6 +129,7 @@ FcreateFDistribution

Numerator degrees of freedom

Denominator degrees of freedom

GammacreateGammaDistribution

Alpha

Beta

HypergeometriccreateHypogeometricDistribution

Population size

Number of successes in population

Sample size

+ Normal (Gaussian)createNormalDistribution

Mean

Standard Deviation

tcreateTDistribution

Degrees of freedom

--------------------------------------------------------------------- To unsubscribe, e-mail: commons-dev-unsubscribe@jakarta.apache.org For additional commands, e-mail: commons-dev-help@jakarta.apache.org