Fit RS generalised lambda distribution to data set using moment matching

Description

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

Usage

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fun.RPRS.mm(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

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 method of 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

Karian, Z. and E. Dudewicz (2000). Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalised Bootstrap Methods. New York, Chapman and Hall.

See Also

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

Examples

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

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