tests whether data is normally distributed using the Cramérvon Mises test.

tests whether data is distributed according to dist using the Cramérvon Mises test.

returns the value of .

Details and OptionsDetails and Options

  • CramerVonMisesTest performs the Cramérvon Mises goodness-of-fit test with null hypothesis that data was drawn from a population with distribution dist 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 dist can be any symbolic distribution with numeric and symbolic parameters or a dataset.
  • The data can be univariate or multivariate .
  • The Cramérvon Mises test assumes that the data came from a continuous distribution.
  • The Cramérvon Mises test effectively uses a test statistic based on the expectation value of where is the empirical CDF of data and is the CDF of dist.
  • For univariate data, the test statistic is given by .
  • For multivariate tests, the sum of the univariate marginal -values is used and is assumed to follow a UniformSumDistribution under .
  • CramerVonMisesTest[data,dist,"HypothesisTestData"] returns a HypothesisTestData object htd that can be used to extract additional test results and properties using the form htd["property"].
  • CramerVonMisesTest[data,dist,"property"] can be used to directly give the value of .
  • Properties related to the reporting of test results include:
  • "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
  • 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:
  • MethodAutomaticthe method to use for computing -values
    SignificanceLevel0.05cutoff 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 .
  • With the setting Method->"MonteCarlo", datasets of the same length as the input are generated under using the fitted distribution. The empirical distribution from CramerVonMisesTest[si,dist,"TestStatistic"] is then used to estimate the -value.
Introduced in 2010
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