Fit FMKL generalised lambda distribution to data set using maximum likelihood estimation

Description

This function fits FMKL generalised lambda distribution to data set using maximum likelihood estimation.

Usage

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fun.RMFMKL.ml(data, fmkl.init = c(-0.25, 1.5), leap = 3,FUN="runif.sobol",
no=10000)

Arguments

data

Dataset to be fitted

fmkl.init

Initial values for FMKL distribution optimization, c(-0.25,1.5) tends to work well.

leap

Scrambling (0,1,2,3) for the Sobol sequence for the distribution fit. See scrambling/leap argument for runif.sobol, runif.halton or QUnif.

FUN

A character string of either "runif.sobol" (default), "runif.halton" or "QUnif".

no

Number of initial random values to find the best initial values for optimisation.

Details

This function provides one of the definitive fit to data set using generalised lambda distributions.

Value

A vector representing four parameters of the FMKL generalised lambda distribution.

Author(s)

Steve Su

References

Su, S. (2007). Numerical Maximum Log Likelihood Estimation for Generalized Lambda Distributions. Journal of Computational statistics and data analysis 51(8) 3983-3998.

Su (2007). Fitting Single and Mixture of Generalized Lambda Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R. Journal of Statistical Software: *21* 9.

See Also

fun.RPRS.ml, fun.data.fit.ml, fun.data.fit.qs

Examples

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## Fitting the normal distribution
# fun.RMFMKL.ml(data=rnorm(1000,2,3),fmkl.init=c(-0.25,1.5),leap=3)

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