gpd | R Documentation |
Density function, distribution function, quantile function and random generation for the generalized Pareto distribution (GPD) with location, scale and shape parameters.
dgpd(x, loc=0, scale=1, shape=0, log = FALSE)
pgpd(q, loc=0, scale=1, shape=0, lower.tail = TRUE)
qgpd(p, loc=0, scale=1, shape=0, lower.tail = TRUE)
rgpd(n, loc=0, scale=1, shape=0)
x , q |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
Number of observations. |
loc , scale , shape |
Location, scale and shape parameters; the
|
log |
Logical; if |
lower.tail |
Logical; if |
The generalized Pareto distribution function (Pickands, 1975) with
parameters \code{loc} = a
, \code{scale} = b
and
\code{shape} = s
is
G(z) = 1 - \{1+s(z-a)/b\}^{-1/s}
for 1+s(z-a)/b > 0
and z > a
, where b > 0
.
If s = 0
the distribution is defined by continuity.
dgpd
gives the density function, pgpd
gives the
distribution function, qgpd
gives the quantile function,
and rgpd
generates random deviates.
Pickands, J. (1975) Statistical inference using extreme order statistics. Annals of Statistics, 3, 119–131.
fpot
, rgev
dgpd(2:4, 1, 0.5, 0.8)
pgpd(2:4, 1, 0.5, 0.8)
qgpd(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
rgpd(6, 1, 0.5, 0.8)
p <- (1:9)/10
pgpd(qgpd(p, 1, 2, 0.8), 1, 2, 0.8)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
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