lmomco (version 2.4.14)

parglo: Estimate the Parameters of the Generalized Logistic Distribution

Description

This function estimates the parameters of the Generalized Logistic distribution given the L-moments of the data in an L-moment object such as that returned by lmoms. The relations between distribution parameters and L-moments are seen under lmomglo.

Usage

parglo(lmom, checklmom=TRUE, ...)

Value

An R

list is returned.

type

The type of distribution: glo.

para

The parameters of the distribution.

source

The source of the parameters: “parglo”.

Arguments

lmom

An L-moment object created by lmoms or vec2lmom.

checklmom

Should the lmom be checked for validity using the are.lmom.valid function. Normally this should be left as the default and it is very unlikely that the L-moments will not be viable (particularly in the \(\tau_4\) and \(\tau_3\) inequality). However, for some circumstances or large simulation exercises then one might want to bypass this check.

...

Other arguments to pass.

Author

W.H. Asquith

References

Hosking, J.R.M., 1990, L-moments---Analysis and estimation of distributions using linear combinations of order statistics: Journal of the Royal Statistical Society, Series B, v. 52, pp. 105--124.

Hosking, J.R.M., 1996, FORTRAN routines for use with the method of L-moments: Version 3, IBM Research Report RC20525, T.J. Watson Research Center, Yorktown Heights, New York.

Hosking, J.R.M., and Wallis, J.R., 1997, Regional frequency analysis---An approach based on L-moments: Cambridge University Press.

See Also

lmomglo, cdfglo, pdfglo, quaglo

Examples

lmr <- lmoms(rnorm(20))
parglo(lmr)
if (FALSE) {
# A then Ph.D. student, L. Read inquired in February 2014 about the relation between
# GLO and the "Log-Logistic" distributions:
par.glo  <- vec2par(c(10, .56, 0), type="glo")         # Define GLO parameters
par.lnlo <- c(exp(par.glo$para[1]), 1/par.glo$para[2]) # Equivalent LN-LO parameters
F <- nonexceeds(); qF <- qnorm(F) # use a real probability axis to show features
plot(qF, exp(quaglo(F, par.glo)), type="l", lwd=5, xaxt="n", log="y",
     xlab="", ylab="QUANTILE") # notice the exp() wrapper on the GLO quantiles
lines(qF, par.lnlo[1]*(F/(1-F))^(1/par.lnlo[2]), col=2, lwd=2) # eq. for LN-LO
add.lmomco.axis(las=2, tcl=0.5, side.type="RI", otherside.type="NPP")
}