GPD {QRMlib} | R Documentation |
Cumulative probability, quantiles, density and random generation from the generalized Pareto distribution.
pGPD(q, xi, beta=1) qGPD(p, xi, beta=1) dGPD(x, xi, beta=1, logvalue=FALSE) rGPD(n, xi, beta=1)
x |
vector of values at which to evaluate density |
q |
vector of quantiles |
p |
vector of probabilities |
n |
sample size |
xi |
shape parameter |
beta |
scale parameter |
logvalue |
whether or not log values of density should be returned (useful for ML) |
Probability (pGPD), quantile (qGPD), density (dGPD) or random sample (rGPD) for the GPD with shape xi.
documentation by Scott Ulman for R-language distribution
## Not run: #Build a loglikelihood function for MLE which can be called from optim() negloglik <- function(theta) { -sum(dGPD(excesses.nl,theta[1],abs(theta[2]),logvalue=TRUE)); } ## End(Not run)