Description Usage Arguments Details Value References See Also Examples

Kuiper test providing a comparison of a fitted distribution with the empirical distribution.

1 |

`x` |
a numeric vector of data values |

`distn` |
character string naming the null distribution |

`fit` |
list of distribution parameters |

`H` |
a treshold value |

`sim` |
maximum number of szenarios in the Monte-Carlo simulation |

`tol` |
if the difference of two subsequent p-value calculations is lower than |

`estfun` |
an function as character string or |

The Kolmogorov-Smirnov test compares the null distribution with the empirical distribution
of the observed data, where left truncated data samples are allowed.
The test statistic (see `ks.test`

) is given
by *KS = max(KS+, KS-)*.

A list with class "mchtest" containing the following components

`statistic` |
the value of the Kuiper statistic |

`treshold` |
the treshold value |

`p.value` |
the p-value of the test |

`data.name` |
a character string giving the name of the data |

`method` |
the character string "Kuiper test" |

`sim.no` |
number of simulated szenarios in the Monte-Carlo simulation |

Chernobay, A., Rachev, S., Fabozzi, F. (2005), *Composites goodness-of-fit tests
for left-truncated loss samples*, Tech. rep., University of Calivornia Santa Barbara

`ks.test`

, `ad.test`

, `adup.test`

for other supremum class tests and `ad2.test`

, `ad2up.test`

,
`w2.test`

for quadratic class tests. For more details see `mctest`

.

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