
Density, distribution function, quantile function and random variate generation for the (generalized) Pareto distribution (GPD).
dGPD(x, shape, scale, log = FALSE)
pGPD(q, shape, scale, lower.tail = TRUE, log.p = FALSE)
qGPD(p, shape, scale, lower.tail = TRUE, log.p = FALSE)
rGPD(n, shape, scale)dPar(x, shape, scale = 1, log = FALSE)
pPar(q, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)
qPar(p, shape, scale = 1, lower.tail = TRUE, log.p = FALSE)
rPar(n, shape, scale = 1)
dGPD()
computes the density, pGPD()
the distribution
function, qGPD()
the quantile function and rGPD()
random
variates of the generalized Pareto distribution.
Similary for dPar()
, pPar()
, qPar()
and
rPar()
for the Pareto distribution.
vector of quantiles.
vector of probabilities.
number of observations.
GPD shape parameter
GPD scale parameter
logical
; if TRUE
(default)
probabilities are
logical; if TRUE
, probabilities p
are
given as log(p)
.
Marius Hofert
The distribution function of the generalized Pareto distribution is
given by
The distribution function of the Pareto distribution is given by
In contrast to dGPD()
, pGPD()
, qGPD()
and
rGPD()
, the functions dPar()
, pPar()
,
qPar()
and rPar()
are vectorized in their main
argument and the parameters.
McNeil, A. J., Frey, R., and Embrechts, P. (2015). Quantitative Risk Management: Concepts, Techniques, Tools. Princeton University Press.
## Basic sanity checks
curve(dGPD(x, shape = 0.5, scale = 3), from = -1, to = 5)
plot(pGPD(rGPD(1000, shape = 0.5, scale = 3), shape = 0.5, scale = 3)) # should be U[0,1]
Run the code above in your browser using DataLab