pareto2.goftest: Goodness-of-fit test for the Pareto-II distribution

Description

Performs goodness-of-fit test for the Pareto-II distribution basing on MLE or MMSE estimates (Zhang, Stevens, 2009) and the Anderson-Darling or Kolmogorov test.

Usage

pareto2.goftest(x, k, s, method=c("anderson-darling", "kolmogorov"))

Arguments

a non-negative numeric vector of data values.

scale parameter, $k>0$ or NULL.

shape parameter, $s>0$ or NULL.

method

either "anderson-darling" or "kolmogorov".

Value

The list of class htest with the following components is passed as a result: ll{ statistic the value of the test statistic. p.value the p-value of the test. alternative a character string describing the alternative hypothesis. method a character string indicating what type of test was performed. data.name a character string giving the name(s) of the data. }

Details

This method, proposed e.g. by Zhang and Stevens (2009), uses either the function ad.test from package ADGofTest or ks.test to compute the selected test.

If k and s are NULL, it bases on bayesian MMS estimators, see pareto2.zsestimate. If s is not NULL, then the unbiased maximum likelihood estimator is used to determine the scale parameter (see pareto2.mlekestimate) iff it is not given.

References

Zhang J., Stevens M.A., A New and Efficient Estimation Method for the Generalized Pareto Distribution, Technometrics 51(3), 2009, 316-325.