GLDEX (version 2.0.0.9.3)

fun.RPRS.qs: Fit RS generalised lambda distribution to data set using quantile matching

Description

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

Usage

fun.RPRS.qs(data, rs.init = c(-1.5, 1.5), leap = 3, FUN = "runif.sobol", 
trial.n = 100, len = 1000, type = 7, no = 10000)

Value

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

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".

trial.n

Number of evenly spaced quantile ranging from 0 to 1 to be used in the checking phase, to find the best set of initial values for optimisation, this is intended to be lower than len to speed up the fitting algorithm. Default is 100.

len

Number of evenly spaced quantile ranging from 0 to 1 to be used, default is 1000

type

Type of quantile to be used, default is 7, see quantile

no

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

Author

Steve Su

Details

This function provides quantile matching 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.

References

Su (2008). Fitting GLD to data via quantile matching method. (Book chapter to appear)

See Also

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

Examples

# \donttest{
# Fitting the normal distribution
 fun.RPRS.qs(data=rnorm(1000,2,3),rs.init=c(-1.5,1.5),leap=3)
# }