fun.RPRS.lm {GLDEX}

Fit RS generalised lambda distribution to data set using L moment matching

Description

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

Usage

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

Arguments

data

Dataset to be fitted

rs.init

Initial values for RS distribution optimization, c(-1.5,1.5) 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.

Details

This function provides method of L moment fitting scheme for RS 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 RS generalised lambda distribution.

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

Value

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

Author(s)

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

Examples

# Fitting the normal distribution
 fun.RPRS.lm(data=rnorm(1000,2,3),rs.init=c(-1.5,1.5),leap=3)