gpd {evir} | R Documentation |
Returns an object of class "gpd"
representing the fit of
a generalized Pareto model to excesses over a high threshold.
gpd(data, threshold = NA, nextremes = NA, method = c("ml", "pwm"), information = c("observed", "expected"), ...)
data |
data vector |
threshold |
a threshold value (either this or
nextremes must be given but not both) |
nextremes |
the number of upper extremes to be used (either
this or threshold must be given but not both) |
method |
whether parameters should be estimated by the maximum
likelihood method "ml" or the probability-weighted moments
method "pwm" |
information |
whether standard errors should be calculated with
"observed" or "expected" information. This only applies
to the maximum likelihood method; for the probability-weighted moments
method "expected" information is used if possible |
... |
arguments passed to optim |
The function uses the general purpose optimization function
optim
when method = "ml"
is chosen.
An object of class "gpd"
describing the fit and including
parameter estimates and standard errors.
Parameter and quantile estimation for the generalized Pareto distribution, JRM Hosking and JR Wallis, Technometrics 29(3), pages 339-349, 1987.
data(danish) out <- gpd(danish, 10) # Fits GPD to excess losses over 10 for the Danish # fire insurance data