tests whether the vectors v1 and v2 are independent.
tests whether the matrices m1 and m2 are independent.
returns the value of "property".
Details and Options
- IndependenceTest performs a hypothesis test on v1 and v2 with null hypothesis that the vectors are independent, and alternative hypothesis that they are not.
- By default, a probability value or -value is returned.
- A small -value suggests that it is unlikely that is true.
- The arguments v1 and v2 can be any real-valued vectors or matrices of equal length.
- IndependenceTest[v1,v2] will choose the most powerful test that applies to v1 and v2.
- IndependenceTest[v1,v2,All] will choose all tests that apply to v1 and v2.
- IndependenceTest[v1,v2,"test"] reports the -value according to "test".
- Some of the available tests assume normality for the vi. Some tests are restricted to vectors. Most tests are restricted to tests of monotonic or linear independence.
- The following tests can be used:
"BlomqvistBeta" monotonic based on Blomqvist's "GoodmanKruskalGamma" monotonic, vector based on the -coefficient "HoeffdingD" vector based on Hoeffding's "KendallTau" monotonic based on Kendall's "PearsonCorrelation" linear, normality, vector based on Pearson product-moment "PillaiTrace" normality, linear based on Pillai's trace "SpearmanRank" monotonic based on Spearman's "WilksW" normality, linear based on Wilks'
- IndependenceTest[v1,v2,"HypothesisTestData"] returns a HypothesisTestData object htd that can be used to extract additional test results and properties using the form htd["property"].
- IndependenceTest[v1,v2,"property"] can be used to directly give the value of "property".
- Properties related to the reporting of test results include:
"AllTests" list of all applicable tests "AutomaticTest" test chosen if Automatic is used "DegreesOfFreedom" the degrees of freedom used in a test "PValue" list of -values "PValueTable" formatted table of -values "ShortTestConclusion" a short description of the conclusion of a test "TestConclusion" a description of the conclusion of a test "TestData" list of pairs of test statistics and -values "TestDataTable" formatted table of -values and test statistics "TestStatistic" list of test statistics "TestStatisticTable" formatted table of test statistics
- The following options can be used:
AlternativeHypothesis "Unequal" the inequality for the alternative hypothesis MaxIterations Automatic max iterations for multivariate nonparametric tests Method Automatic the method to use for computing -values SignificanceLevel 0.05 cutoff for diagnostics and reporting VerifyTestAssumptions Automatic what assumptions to verify
- For tests of independence, a cutoff is chosen such that is rejected only if . The value of used for the "TestConclusion" and "ShortTestConclusion" properties is controlled by the SignificanceLevel option. This value is also used in diagnostic tests of normality. By default, is set to 0.05.
- Named settings for VerifyTestAssumptions in IndependenceTest include:
"Normality" verify that all data is normally distributed
Examplesopen allclose all
Basic Examples (2)
Using Automatic applies the most powerful appropriate test for linear independence:
Create a HypothesisTestData object for repeated property extraction:
Extract some properties from the HypothesisTestData object:
Properties & Relations (4)
To test particular values of correlation or rank correlation, use CorrelationTest:
HoeffdingDTest should be used if nonlinear dependency is expected:
IndependenceTest does not detect this by default:
HoeffdingD is sensitive to many types of dependence:
Wolfram Research (2012), IndependenceTest, Wolfram Language function, https://reference.wolfram.com/language/ref/IndependenceTest.html.
Wolfram Language. 2012. "IndependenceTest." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/IndependenceTest.html.
Wolfram Language. (2012). IndependenceTest. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/IndependenceTest.html