GLDrs: Generalized Lambda Distribution (GLD) RS parameterization

In dmi3kno/qpd: Tools for Quantile-Parametrized Distribiutions

Generalized Lambda Distribution (GLD) RS parameterization

Description

Quantile function, quantile density, density quantile and inverse quantile functions for GLD distribution with RS parameterization. aGLDrs_mean and aGLDrs_median are theoretical mean and median, which can be used for adjusting the quantile likelihood.

Usage

qGLDrs(u, l1, l2, l3, l4)

fGLDrs(u, l1, l2, l3, l4)

dqGLDrs(u, l1, l2, l3, l4, log = FALSE)

rGLDrs(n, l1, l2, l3, l4)

pGLDrs(q, ..., lower = 0, upper = 1, tol = 1e-06, silent = TRUE, trace = 0)

is_GLDrs_valid(l1, l2, l3, l4)

aGLDrs_mean(l1, l2, l3, l4)

aGLDrs_median(l1, l2, l3, l4)

Arguments

u	numeric vector of probabilities
l1	GLD parameter \lambda_1
l2	GLD parameter \lambda_2
l3	GLD parameter \lambda_3
l4	GLD parameter \lambda_4
log	should the log density be returned. Default=FALSE
n	numeric number of samples to draw
q	vector of quantiles
...	used by method
lower, upper	the stats::uniroot lower and upper end points of the interval to be searched. Defaults are 0 and 1, respectively
tol	the stats::uniroot desired accuracy (convergence tolerance). Default value 1e-06
silent	the base::try argument. Default is TRUE
trace	integer number passed to stats::uniroot; if positive, tracing information is produced. Higher values giving more details.

Value

quantiles, QDF, DQF, random samples or probabilities of GLD

Examples

p_grd <- make_pgrid()
is_GLDrs_valid(1, -1, -1/8, -1/32)
qGLDrs(p_grd, 1, -1, -1/8, -1/32)

dmi3kno/qpd documentation built on Sept. 29, 2024, 6:39 p.m.