GLDEX: fun.comp.moments.ml – R documentation

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fun.comp.moments.ml

Compare the moments of the data and the fitted univariate generalised lambda distribution.

Description

After fitting the distribution, it is often desirable to see whether the moments of the data matches with the fitted distribution. This function computes the theoretical and actual moments especially for fun.data.fit.ml function output.

Usage

fun.comp.moments.ml(theo.obj, data, name = "ML")

Arguments

`theo.obj`	Fitted distribution parameters, usually output from `fun.data.fit.ml`
`data`	Data set used
`name`	Naming the method used in fitting the distribution, by default this is "ML".

Value

`r.mat`	A matrix showing the mean, variance, skewness and kurtosis of the fitted distribution in comparison to the data set.
`eval.mat`	Absolute difference in each of the four moments from the data under each of the distibutional fits.

Note

Sometimes it is difficult to find RPRS type of fits to data set, so instead fun.comp.moments.ml.2 is used to compare the theoretical moments of RMFMKL.ML and STAR methods with respect to the dataset fitted.

Author(s)

Steve Su

Examples

## Generate random normally distributed observations.
# junk<-rnorm(1000,3,2)

## Fit the dataset using fun.data.ml
# fit<-fun.data.fit.ml(junk)

## Compare the resulting fits. It is usually the case the maximum likelihood 
## provides better estimation of the moments than the starship method.
# fun.comp.moments.ml(fit,junk)

GLDEX

Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods

v2.0.0.7

GPL (>= 3)

Authors

Steve Su, with contributions from: Diethelm Wuertz, Martin Maechler and Rmetrics core team members for low discrepancy algorithm, Juha Karvanen for L moments codes, Robert King for gld C codes and starship codes, Benjamin Dean for corrections and input in ks.gof code and R core team for histsu function.

Initial release

2020-02-04