Description Usage Arguments Details Value References Examples

This function computes the goodness-of-fit test for the gamma family in the spirit of Cramer and von Mises. Note that this tests the composite hypothesis of fit to the family of gamma distributions, i.e. a bootstrap procedure is implemented to perform the test.

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`data` |
a vector of positive numbers. |

`boot` |
number of bootstrap iterations used to obtain critical value. |

`alpha` |
level of significance of the test. |

The CramÃ©r-von Mises test is computed as described in Henze et. al. (2012). Critical values are obtained by a parametric bootstrap procedure, see `crit.values`

.

a list containing the value of the test statistic, the approximated critical value and a test decision on the significance level `alpha`

:

`$T.value`

the value of the test statistic.

`$cv`

the approximated critical value.

`$par.est`

number of points used in approximation.

`$Decision`

the comparison of the critical value and the value of the test statistic.

`$sig.level`

level of significance chosen.

`$boot.run`

number of bootstrap iterations.

Henze, N., Meintanis, S.G., Ebner, B. (2012) "Goodness-of-fit tests for the Gamma distribution based on the empirical Laplace transform". Communications in Statistics - Theory and Methods, 41(9): 1543-1556. DOI

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