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## Copyright (C) 2020 Berent Lunde
## License: GPL-3
# The Gumbel probability density function.
# Its documentation is combined with gumbel-doc
#
#' @rdname pgumbel
#' @export
dgumbel <- function(x, location = 0, scale = 1, log = FALSE, grad=FALSE){
# check input
error_messages <- c()
error_messages_type <- c(
"x" = "\n Error: x must be a scalar or vector of type numeric",
"location" = "\n Error: location must be a real number",
"scale" = "\n Error: scale must be a positive real number",
"log" = "\n Error: log must be of type logical with length 1",
"grad" = "\n Error: grad must be of type logical with length 1"
)
# check x
if(!is.vector(x, mode="numeric")){
error_messages <- c(error_messages, error_messages_type["x"])
}
# check location
if(is.numeric(location) && length(location)==1){
#ok
}else{
error_messages <- c(error_messages, error_messages_type["location"])
}
# check scale
if(is.numeric(scale) && length(scale)==1 && scale > 0){
#ok
}else{
error_messages <- c(error_messages, error_messages_type["scale"])
}
# check log
if(is.logical(log) && length(log)==1){
#ok
}else{
# error
error_messages <- c(error_messages, error_messages_type["log"])
}
# check grad
if(is.logical(grad) && length(grad)==1){
#ok
}else{
# error
error_messages <- c(error_messages, error_messages_type["grad"])
}
# Any error messages?
if(length(error_messages)>0)
stop(error_messages)
# if ok
if(!grad){
res <- .dgumbel(x, location=location, scale=scale, log_dens=log)
}else{
res <- .ddgumbel(x, location=location, scale=scale, log_dens=log)
}
return(res)
}
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