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# ============================ fExtremes::gpdFit ============================ #
# Methods for class fExtremes_gpd
#' @export
logLikVec.fExtremes_gpd <- function(object, pars = NULL, ...) {
if (!missing(...)) {
warning("extra arguments discarded")
}
# If the parameter estimates have not been provided in pars then extract
# them from the fitted object
if (is.null(pars)) {
pars <- coef(object)
}
n_pars <- length(pars)
response_data <- object@fit$data
sigma <- pars["beta"]
xi <- pars["xi"]
# Calculate the loglikelihood contributions
if (sigma <= 0) {
val <- -Inf
} else {
val <- revdbayes::dgp(response_data, loc = object@fit$threshold,
scale = sigma, shape = xi, log = TRUE)
}
# Return the usual attributes for a "logLik" object
attr(val, "nobs") <- nobs(object)
attr(val, "df") <- length(pars)
class(val) <- "logLikVec"
return(val)
}
#' @export
nobs.fExtremes_gpd <- function(object, ...) {
return(sum(object@fit$data > object@fit$threshold))
}
#' @export
coef.fExtremes_gpd <- function(object, ...) {
return(object@fit$par.ests)
}
#' @export
vcov.fExtremes_gpd <- function(object, ...) {
vc <- object@fit$varcov
par_names <- names(coef(object))
dimnames(vc) <- list(par_names, par_names)
return(vc)
}
#' @export
logLik.fExtremes_gpd <- function(object, ...) {
return(logLik(logLikVec(object)))
}
# See fExtremes_methods.R for nobs, coef, vcov, logLik methods for
# class "fGPDFIT"
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