fit.gld {gb}

Fitting a Ramberg-Schmeiser-Tukey (RST) lambda distribution

Description

To fit a Ramberg-Schmeiser-Tukey (RST) lambda distribution with the three moment-matching methods.

Usage

  fit.gld(x,method='LMoM')

Arguments

x

A sample of size at least 6. 'NA' values will be automatically removed.

method

Choose GLD fitting method. Default: 'LMoM'. Other options: 'MoM'– method of moments; "MoP", method of percentiles; "LMoM", method of L-moments. 'best' chooses the best fit from the above three methods, which takes a while.

Author(s)

B. Wang [e-mail]

References

Karian, Z.A., Dudewicz, E.J., McDonald, P., 1996. The Extended Generalized Lambda Distribution System for Fitting Distributions to Data: history,completion of theory, tables, applications, the “final word” on moment fits, Comm. in Statist.- Simul. \& Comput. 25(3), 611-642.

Karian, Z.A., Dudewicz, E.J., 2000. Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalized Bootstrap Methods, Chapman and Hall/CRC.

See Also

fit.egld, qrsgld,prsgld, rrsgld,drsgld.

Examples

mu = 34.5; sig=1.5
y = rnorm(1000,mu,sig)
x = round(y)  ###  rounding errors

x0 = seq(min(y),max(y),length=100)
f0 = dnorm(x0,mu,sig)
plot(f0~x0,type='l')
lines(density(y),col=4)
## fit with method of moments
(out1 = fit.gld(x, method='MoM')) 
lines(out1,col=2)
##  Method of percentile
(out2 = fit.gld(x, method='mop'))
lines(out2, col=3)
## Method of L-moments
(out3 = fit.gld(x, method='lmom'))
lines(out3, col=5)
##  Fitting EGLD
(out0 = fit.egld(x))
lines(out0,col=6)

legend(max(x0), max(f0), xjust=1,yjust=1,
  legend=c("true","kde","MoM","MoP","LMoM","egld"),
  lty=c(1,1,1,1,1,1),
  col=c(1,4,2,3,5,6))