gpdUC: The Generalized Pareto Distribution

Description

Density, distribution function, quantile function and random generation for the generalized Pareto distribution (GPD) with location parameter location, scale parameter scale and shape parameter shape.

Usage

dgpd(x, location = 0, scale = 1, shape = 0, log = FALSE,
     tolshape0 = sqrt(.Machine$double.eps))
pgpd(q, location = 0, scale = 1, shape = 0,
     lower.tail = TRUE, log.p = FALSE)
qgpd(p, location = 0, scale = 1, shape = 0,
     lower.tail = TRUE, log.p = FALSE)
rgpd(n, location = 0, scale = 1, shape = 0)

Value

dgpd gives the density,

pgpd gives the distribution function,

qgpd gives the quantile function, and

rgpd generates random deviates.

Arguments

x, q: vector of quantiles.
p: vector of probabilities.
n: number of observations. If length(n) > 1 then the length is taken to be the number required.
location: the location parameter \(\mu\).
scale: the (positive) scale parameter \(\sigma\).
shape: the shape parameter \(\xi\).
log: Logical. If log = TRUE then the logarithm of the density is returned.
lower.tail, log.p: Same meaning as in punif or qunif.
tolshape0: Positive numeric. Threshold/tolerance value for resting whether \(\xi\) is zero. If the absolute value of the estimate of \(\xi\) is less than this value then it will be assumed zero and an exponential distribution will be used.

Author

T. W. Yee and Kai Huang

Details

See gpd, the VGAM family function for estimating the two parameters by maximum likelihood estimation, for formulae and other details. Apart from n, all the above arguments may be vectors and are recyled to the appropriate length if necessary.

References

Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. London: Springer-Verlag.

Examples

Run this code

if (FALSE)  loc <- 2; sigma <- 1; xi <- -0.4
x <- seq(loc - 0.2, loc + 3, by = 0.01)
plot(x, dgpd(x, loc, sigma, xi), type = "l", col = "blue",
     main = "Blue is density, red is the CDF", ylim = c(0, 1),
     sub = "Purple are 5,10,...,95 percentiles", ylab = "", las = 1)
abline(h = 0, col = "blue", lty = 2)
lines(qgpd(seq(0.05, 0.95, by = 0.05), loc, sigma, xi),
  dgpd(qgpd(seq(0.05, 0.95, by = 0.05), loc, sigma, xi), loc, sigma, xi),
      col = "purple", lty = 3, type = "h")
lines(x, pgpd(x, loc, sigma, xi), type = "l", col = "red")
abline(h = 0, lty = 2)

pgpd(qgpd(seq(0.05, 0.95, by = 0.05), loc, sigma, xi), loc, sigma, xi)

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