# R/endPoint.R In texmex: Statistical Modelling of Extreme Values

#### Documented in endPointendPoint.evmOptendPoint.evmSim

```#' Calculate upper end point for a fitted extreme value model
#'
#' Calculate upper end point for fitted extreme value model
#'
#'
#' @aliases endPoint endPoint.evmOpt endPoint.evmSim endPoint.evmBoot
#' @usage endPoint(y, verbose=TRUE, .unique=TRUE, ...)
#'
#' \method{endPoint}{evmOpt}(y,verbose=TRUE, .unique=TRUE, ...)
#' \method{endPoint}{evmSim}(y,verbose=TRUE, .unique=TRUE, ...)
#' @param y Object of class \code{evmOpt} or \code{evmSim}, as returned by
#' @param verbose Whether to print output.
#' @param .unique Whether or not to use only unique values of \code{y}.
#' @param ... further arguments to be passed to the \code{\link{signif}}
#' function.
#' @return In cases where the fitted shape parameter is negative, the fitted
#' finite upper endpoint of the extreme value model.
#' @author Janet E. Heffernan
#' @export endPoint
endPoint <- function(y,verbose=TRUE,.unique=TRUE,...){
UseMethod("endPoint", y)
}

#' @export
endPoint.evmOpt <- function(y, verbose=TRUE,.unique=TRUE,...){

if(.unique) Unique <- unique else Unique <- identity

p <- texmexMakeParams(coef(y), y\$data\$D)
endpoint <- y\$family\$endpoint

negShape <- p[, ncol(p)] < 0

if(any(negShape)){
UpperEndPoint <- endpoint(p, y)
UpperEndPoint[!negShape] <- Inf
if(verbose){
o <- Unique(cbind(y\$data\$D[['xi']], p))
print(signif(o,...))
} else {
invisible(Unique(UpperEndPoint))
}
} else {
Unique(rep(Inf,length(negShape)))
}
}

#' @export
endPoint.evmSim <- function(y,verbose=TRUE,.unique=TRUE,...){
endPoint(y\$map,verbose=verbose,.unique=.unique,...)
}

#' @export
endPoint.evmBoot <- endPoint.evmSim
```

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texmex documentation built on May 29, 2017, 6:42 p.m.