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
- SpearmanRankTest 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.
- SpearmanRankTest is based on Spearman's rank correlation computed by SpearmanRho[v1,v2].
- For testing matrices the test statistic is based on inner standardized spatial ranks and asymptotically follows a ChiSquareDistribution[r*s] where r and s are the dimension of m1 and m2, respectively. The test is invariant under affine transformations.
- SpearmanRankTest[v1,v2,"HypothesisTestData"] returns a HypothesisTestData object htd that can be used to extract additional test results and properties using the form htd["property"].
- SpearmanRankTest[v1,v2,"property"] can be used to directly give the value of "property".
- Properties related to the reporting of test results include:
"DegreesOfFreedom" the degrees of freedom used in the test "PValue" the -value of the test "PValueTable" formatted table containing the -value "ShortTestConclusion" a short description of the conclusion of the test "TestConclusion" a description of the conclusion of the test "TestData" a list containing the test statistic and -value "TestDataTable" formatted table of the -value and test statistic "TestStatistic" the test statistic "TestStatisticTable" formatted table containing the test statistic
- The following options can be used:
AlternativeHypothesis "Unequal" the inequality for the alternative hypothesis MaxIterations Automatic max iterations for multivariate test Method Automatic the method to use for computing -values SignificanceLevel 0.05 cutoff for diagnostics and reporting
- 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. By default is set to 0.05.
Examplesopen allclose all
Basic Examples (2)
Create a HypothesisTestData object for repeated property extraction:
Extract some properties from the HypothesisTestData object:
Properties & Relations (9)
For vector-to-vector comparisons the test statistic is computed as SpearmanRho:
The test statistic follows a StudentTDistribution[n-2] under :
In higher dimensions the test statistic follows a ChiSquareDistribution[r*s]:
To test a particular value of Spearman's use CorrelationTest:
IndependenceTest can be used to select an appropriate test of independence:
SpearmanRankTest is one of the available tests:
SpearmanRankTest only detects monotonic dependence:
HoeffdingDTest can be used to detect a wider variety of dependence structures:
The Spearman rank test works with the values only when the input is a TimeSeries:
The Spearman rank test works with all the values together when the input is a TemporalData:
Wolfram Research (2012), SpearmanRankTest, Wolfram Language function, https://reference.wolfram.com/language/ref/SpearmanRankTest.html.
Wolfram Language. 2012. "SpearmanRankTest." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/SpearmanRankTest.html.
Wolfram Language. (2012). SpearmanRankTest. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/SpearmanRankTest.html