parglo | R Documentation |
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
.
parglo(lmom, checklmom=TRUE, ...)
lmom |
An L-moment object created by |
checklmom |
Should the |
... |
Other arguments to pass. |
An R list
is returned.
type |
The type of distribution: |
para |
The parameters of the distribution. |
source |
The source of the parameters: “parglo”. |
W.H. Asquith
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.
lmomglo
, cdfglo
, pdfglo
, quaglo
lmr <- lmoms(rnorm(20))
parglo(lmr)
## Not run:
# 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")
## End(Not run)
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