GLDEX (version 2.0.0.9.3)

fun.RMFMKL.lm: Fit FMKL generalised lambda distribution to data set using L moment matching

Description

This function fits FMKL generalised lambda distribution to data set using L moment matching

Usage

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

Value

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

Arguments

data

Dataset to be fitted

fmkl.init

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

leap

See scrambling argument in fun.gen.qrn.

FUN

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

no

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

Author

Steve Su

Details

This function provides method of L moment fitting scheme for FMKL GLD. Note this function can fail if there are no defined percentiles from the data set or if the initial values do not lead to a valid FMKL generalised lambda distribution.

This function is based on scheme detailed in the literature below but it has been modified by the author (Steve Su).

References

Asquith, W. (2007). "L-moments and TL-moments of the generalized lambda distribution." Computational Statistics and Data Analysis 51(9): 4484-4496.

Karvanen, J. and A. Nuutinen (2008). "Characterizing the generalized lambda distribution by L-moments." Computational Statistics and Data Analysis 52(4): 1971-1983.

See Also

fun.RMFMKL.ml, fun.RMFMKL.mm, fun.RMFMKL.qs, fun.data.fit.ml fun.data.fit.lm, fun.data.fit.qs, fun.data.fit.mm

Examples

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