GLDEX: fun.moments.bimodal – R documentation

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fun.moments.bimodal

Finds the moments of fitted mixture of generalised lambda distribution by simulation.

Description

This functions compute the mean, variance, skewness and kurtosis of the fitted generalised lambda distribution mixtures using Monte Carlo simulation.

Usage

fun.moments.bimodal(result1, result2, prop1, prop2, len = 1000, 
no.test = 1000, param1, param2)

Arguments

`result1`	A vector comprising four values for the first generalised lambda distribution.
`result2`	A vector comprising four values for the second generalised lambda distribution.
`prop1`	Proportion of the first generalised lambda distribution
`prop2`	1-prop1, this can be left unspecified.
`len`	Length of object for each simulation run.
`no.test`	Number of simulation run.
`param1`	This can be `"rs"` or `"fmkl"`, specifying the type of the first generalised lambda distribution.
`param2`	This can be `"rs"` or `"fmkl"`, specifying the type of the second generalised lambda distribution.

Details

There is also a theoretical computation of the moments in fun.theo.bi.mv.gld, it should be noted that the theoretical moments may not exist. The length of object in len means how many observations should be generated in each simulation run, with the number of simulation runs governed by no.test.

Value

A matrix with four columns showing the mean, variance, skewness and kurtosis of the fitted generalised lambda distribution mixtures using Monte Carlo simulation. Each row represents a simulation run.

Author(s)

Steve Su

Examples

## Fitting the first column of the Old Faithful Geyser data
# fit1<-fun.auto.bimodal.ml(faithful[,1],init1.sel="rmfmkl",init2.sel="rmfmkl",
# init1=c(-0.25,1.5),init2=c(-0.25,1.5),leap1=3,leap2=3)

## After fitting compute the monte carlo moments using fun.moments.bimodal
# fun.moments.bimodal(fit1$par[1:4],fit1$par[5:8],prop1=fit1$par[9],
# param1="fmkl",param2="fmkl")

## It is also possible to compare this with the moments of the original dataset:
# fun.moments(faithful[,1])

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