fld: Flattened Logistic Distribution (FLD)

In dmi3kno/qpd: Tools for Quantile-Parametrized Distribiutions

Flattened Logistic Distribution (FLD)

Description

Defines quantile function (ICDF), probability density and quantile density function as well as probability function (CDF) for flattened logistic distribution

Usage

qfld(p, bt, k, a = 0)

ffld(p, bt, k, a = 0)

dqfld(p, bt, k, a = 0, log = FALSE)

rfld(n, bt, k, a = 0)

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

Arguments

p	vector of probabilities
bt	parameter beta of GFLD distribution (scale). Should be non-negative.
k	parameter k of GFLD distribution (shape). Should be non-negative.
a	location parameter alpha of GFLD distribution(location parameter), default is 0
log	logical; if TRUE, log density is returnes. Default is FALSE
n	numeric; number of samples to draw from FLD distribution
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

vector

Examples

qfld(0.1, 0.5, 0.3, 0.5)
# centered gfld
p <- runif(1e4)
x <- qfld(p, 0.25, 1)-qfld(0.5, 0.25, 1)
hist(x,30)

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