returns the value of .
- MardiaKurtosisTest performs the Mardia kurtosis goodness-of-fit test with null hypothesis that data was drawn from a MultinormalDistribution and alternative hypothesis that it was not.
- By default a probability value or -value is returned.
- A small -value suggests that it is unlikely that the data came from dist.
- The data can be univariate or multivariate .
- The Mardia kurtosis test effectively compares a multivariate measure of kurtosis for data to a MultinormalDistribution.
- MardiaKurtosisTest[data,dist,"HypothesisTestData"] returns a HypothesisTestData object htd that can be used to extract additional test results and properties using the form htd["property"].
- MardiaKurtosisTest[data,dist,"property"] can be used to directly give the value of .
- PearsonChiSquareTest[data,dist,"property"] can be used to directly give the value of .
- Properties related to the reporting of test results include:
"DegreesOfFreedom" the degrees of freedom used in a test "PValue" -value "PValueTable" formatted version of "ShortTestConclusion" a short description of the conclusion of a test "TestConclusion" a description of the conclusion of a test "TestData" test statistic and -value "TestDataTable" formatted version of "TestStatistic" test statistic "TestStatisticTable" formatted
- The following properties are independent of which test is being performed.
- Properties related to the data distribution include:
"FittedDistribution" fitted distribution of data "FittedDistributionParameters" distribution parameters of data
- The following options can be given:
Method Automatic the method to use for computing -values SignificanceLevel 0.05 cutoff for diagnostics and reporting
- For a test for goodness-of-fit, a cutoff is chosen such that is rejected only if . The value of used for the and properties is controlled by the SignificanceLevel option. By default is set to .
- The following methods can be used to compute -values:
Automatic correct for small samples up to dimension 5 "Asymptotic" use the asymptotic distribution of the test statistic "MonteCarlo" use Monte Carlo simulation
- With the setting Method-> "MonteCarlo", datasets of the same length as the input are generated under using the fitted distribution. The EmpiricalDistribution from MardiaKurtosisTest[si,"TestStatistic"] is then used to estimate the -value.
Introduced in 2010