Nothing
#' @rdname mex
#' @export
summary.predict.mex <- function( object, mth, probs=c( .05, .5, .95 ), ... ){
stdev <- function( x ) sqrt( var( x ) )
if ( missing( mth ) ) mth <- object$mth
if (!is.null(object$replicates)){
res <- t( sapply( object$replicates , function ( x ) apply( x, 2, mean ) ) )
}
else {
res <- object$data$simulated
}
# Create summary function
sumfun <- if (!is.null(object$replicates)){
function( x , probs){
c( mean=mean( x ), se=stdev( x ) , quantile( x, probs=probs ) )
}
}
else {
function(x, probs){
c(mean=mean(x), quantile(x, probs=probs))
}
}
ans <- apply( res, 2, sumfun, probs ) # Summary of expected values
dn <- paste( dimnames( object$data$simulated)[[ 2 ]] ,"|", names( object$data$simulated )[[ 1 ]] , ">Q",100*object$pqu, sep="" )
dimnames( ans )[[ 2 ]] <- dn
# Get the threshold exceedence probabilities
if (!is.null(object$replicates)){
thres <- t(sapply(1:(dim(object$replicates[[1]])[[2]]) ,
function(i, x, mth){
x <- sapply(x , function(x, i) x[, i], i=i)
mth <- mth[i]
apply(x , 2, function(x, mth)
mean(x > mth),
mth = mth)
}, x=object$replicates, mth = mth))
thres <- apply( thres, 1, mean)
thres <- matrix( thres, nrow=1 )
}
else {
thres <- sapply(1:dim(object$data$simulated)[[2]], function(i, x, mth){ mean(x[,i] > mth[i]) },
x = object$data$simulated, mth=mth)
thres <- matrix(thres, nrow=1)
}
wn <- dimnames( object$data$simulated )[[ 2 ]][ 1 ]
wth <- paste( "Q", 100*object$pqu, sep = "" )
dn <- paste( "P(", dimnames( object$data$simulated )[[ 2 ]] , ">", signif(mth, ...),"|", wn, ">", wth, ")", sep = "" )
dimnames( thres ) <- list( "", dn )
ans <- list(ans=ans, thres=thres, call=object$call, pqu=object$pqu ,
B = length( object$replicates ),
which = names( object$data$simulated )[[ 1 ]],
statistic=deparse( substitute( statistic ) )
)
oldClass(ans) <- "summary.predict.mex"
ans
}
#' @export
print.summary.predict.mex <- function( x, ... ){
print( x$call, ... )
if (x$B > 0) cat( "\nResults from", x$B, "bootstrap runs.\n" )
cat( paste( "\nConditioned on ", x$which, " being above its ", 100*x$pqu, "th percentile.\n\n", sep = "" ) )
cat( "\nConditional Mean and Quantiles:\n\n" )
print( signif(x$ans,3), ... )
cat( "\nConditional probability of threshold exceedance:\n\n" )
print( signif(x$thres,3), ... )
invisible(x)
}
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