quagpa | R Documentation |
This function computes the quantiles of the Generalized Pareto distribution given parameters (\xi
, \alpha
, and \kappa
) computed by pargpa
. The quantile function is
x(F) = \xi + \frac{\alpha}{\kappa} \left( 1-(1-F)^\kappa \right)\mbox{,}
for \kappa \ne 0
, and
x(F) = \xi - \alpha\log(1-F)\mbox{,}
for \kappa = 0
, where x(F)
is the quantile for nonexceedance probability F
, \xi
is a location parameter, \alpha
is a scale parameter, and
\kappa
is a shape parameter. The range of x
is \xi \le x \le \xi + \alpha/\kappa
if k > 0
; \xi \le x < \infty
if \kappa \le 0
. Note that the shape parameter \kappa
parameterization of the distribution herein follows that in tradition by the greater L-moment community and others use a sign reversal on \kappa
. (The evd package is one example.)
quagpa(f, para, paracheck=TRUE)
f |
Nonexceedance probability ( |
para |
The parameters from |
paracheck |
A logical controlling whether the parameters are checked for validity. Overriding of this check might be extremely important and needed for use of the quantile function in the context of TL-moments with nonzero trimming. |
Quantile value for nonexceedance probability F
.
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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.2517-6161.1990.tb01775.x")}.
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.
cdfgpa
, pdfgpa
, lmomgpa
, pargpa
lmr <- lmoms(c(123, 34, 4, 654, 37, 78))
quagpa(0.5,pargpa(lmr))
## Not run:
# Let us compare L-moments, parameters, and 90th percentile for a simulated
# GPA distibution of sample size 100 having the following parameters between
# lmomco and lmom packages in R. The answers are the same.
gpa.par <- lmomco::vec2par(c(1.02787, 4.54603, 0.07234), type="gpa")
X <- lmomco::rlmomco(100, gpa.par)
lmom::samlmu(X)
lmomco::lmoms(X)
lmom::pelgpa( lmom::samlmu(X))
lmomco::pargpa(lmomco::lmoms(X))
lmom::quagpa(0.90, lmom::pelgpa( lmom::samlmu(X)))
lmomco::quagpa(0.90, lmomco::pargpa(lmomco::lmoms( X))) #
## End(Not run)
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