smile.stat.hypothesis

Class ChiSqTest

java.lang.Object

smile.stat.hypothesis.ChiSqTest

public class ChiSqTest
extends java.lang.Object

Pearson's chi-square test, also known as the chi-square goodness-of-fit test or chi-square test for independence. Note that the chi-square distribution is only approximately valid for large sample size. If a siginficant fraction of bins have small numbers of counts (say, < 10), then it the statistic is not well approximated by a chi-square probability function.

Field Summary

Fields

Modifier and Type	Field and Description
double	chisq chi-square statistic
double	df The degree of freedom of chisq-statistic.
double	pvalue p-value

Method Summary

Modifier and Type	Method and Description
static ChiSqTest	test(int[] bins, double[] prob) One-sample chisq test.
static ChiSqTest	test(int[] bins, double[] prob, int constraints) One-sample chisq test.
static ChiSqTest	test(int[] bins1, int[] bins2) Two-sample chisq test.
static ChiSqTest	test(int[] bins1, int[] bins2, int constraints) Two-sample chisq test.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

df

public double df

The degree of freedom of chisq-statistic.

chisq

public double chisq

chi-square statistic

pvalue

public double pvalue

p-value

Method Detail

test

public static ChiSqTest test(int[] bins,
                             double[] prob)

One-sample chisq test. Given the array bins containing the observed numbers of events, and an array prob containing the expected probabilities of events, and given one constraint, a small value of p-value indicates a significant difference between the distributions.

test

public static ChiSqTest test(int[] bins,
                             double[] prob,
                             int constraints)

One-sample chisq test. Given the array bins containing the observed numbers of events, and an array prob containing the expected probabilities of events, and given the number of constraints (normally one), a small value of p-value indicates a significant difference between the distributions.

test

public static ChiSqTest test(int[] bins1,
                             int[] bins2)

Two-sample chisq test. Given the arrays bins1 and bins2, containing two sets of binned data, and given one constraint, a small value of p-value indicates a significant difference between the distributions.

test

public static ChiSqTest test(int[] bins1,
                             int[] bins2,
                             int constraints)

Two-sample chisq test. Given the arrays bins1 and bins2, containing two sets of binned data, and given the number of constraints (normally one), a small value of p-value indicates a significant difference between the distributions.