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fun.RPRS.mm

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

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

Examples

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

Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods

v2.0.0.7
GPL (>= 3)
Authors
Steve Su, with contributions from: Diethelm Wuertz, Martin Maechler and Rmetrics core team members for low discrepancy algorithm, Juha Karvanen for L moments codes, Robert King for gld C codes and starship codes, Benjamin Dean for corrections and input in ks.gof code and R core team for histsu function.
Initial release
2020-02-04

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