GPD: Create a GPD distribution (Generalized Pareto Distribution)

In benRenard/disTRIMbution: Estimation of Trimmed (Either Truncated or Rectified) Distributions

Create a GPD distribution (Generalized Pareto Distribution)

Description

Create a GPD distribution (Generalized Pareto Distribution)

Usage

GPD(loc = 0, scale = 1, shape = 0)

Arguments

loc	The location parameter, often noted \mu, which represents the threshold above which data are taken. Can be any real number. Defaults to '0'.
scale	The scale parameter, often noted \sigma. Can be any positive number. Defaults to '1'.
shape	The shape parameter, often noted \xi. Can be any real number. Defaults to '0', in which case the GPD distribution correspond to the Exponential distribution. Note that the 'statistical' convention (also used in package evd, in Wikipedia and in many textbooks) is used here: \xi > 0 correspond to heavy-tailed distributions. \xi < 0 correspond to light-tailed, right-bounded distributions. Be aware that the opposite convention is used in some disciplines (typically, Hydrology).

Value

A 'GPD' object.

See Also

Other continuous distributions: GEVmin2(), GEVmin(), GEV(), GPDmin2(), GPDmin(), KDB4(), KDB(), Triangular()

Examples

set.seed(27)

X <- GPD(loc=0,scale=1,shape=0.2)
X

random(X, 10)

pdf(X, 0.7)
log_pdf(X, 0.7)

cdf(X, 0.7)
quantile(X, 0.7)

cdf(X, quantile(X, 0.7))
quantile(X, cdf(X, 0.7))

benRenard/disTRIMbution documentation built on July 1, 2023, 4:24 a.m.