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# =================================== POT =================================== #
#' Loglikelihood adjustment for POT fits
#'
#' S3 \code{alogLik} method to perform loglikelihood adjustment for fitted
#' extreme value model objects returned from
#' \code{\link[POT]{fitGPD}} function in the POT package.
#' The model must have been fitted using maximum likelihood estimation.
#'
#' @inherit alogLik params references
#' @details See \code{\link{alogLik}} for details.
#' @return An object inheriting from class \code{"chandwich"}. See
#' \code{\link[chandwich]{adjust_loglik}}.
#'
#' \code{class(x)} is \code{c("lax", "chandwich", "POT", "pot", "gpd")}.
#' @seealso \code{\link{alogLik}}: loglikelihood adjustment for model fits.
#' @examples
#' # We need the POT package
#' got_POT <- requireNamespace("POT", quietly = TRUE)
#'
#' if (got_POT) {
#' library(POT)
#' # An example from the POT::fitgpd documentation.
#' set.seed(4082019)
#' x <- POT::rgpd(200, 1, 2, 0.25)
#' fit <- fitgpd(x, 1, "mle")
#' adj_fit <- alogLik(fit)
#' }
#' @name POT
NULL
## NULL
#' @rdname POT
#' @export
alogLik.uvpot <- function(x, cluster = NULL, use_vcov = TRUE, ...) {
if (x$est != "MLE") {
stop("Loglikelihood adjustment is only relevant when est = ''mle''")
}
# List of evd objects supported
supported_by_lax <- list(POT_fitgpd = c("uvpot", "pot"))
# Does x have a supported class?
is_supported <- NULL
for (i in 1:length(supported_by_lax)) {
is_supported[i] <- identical(class(x), unlist(supported_by_lax[i],
use.names = FALSE))
}
if (!any(is_supported)) {
stop(paste("x's class", deparse(class(x)), "is not supported"))
}
# Set the class
name_of_class <- names(supported_by_lax)[which(is_supported)]
class(x) <- name_of_class
# Call adj_object() to adjust the loglikelihood
res <- adj_object(x, cluster = cluster, use_vcov = use_vcov, ...)
class(res) <- c("lax", "chandwich", "POT", "pot", "gpd")
return(res)
}
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