Nothing
`plot.predict.mex` <-
function( x, pch=c( 1, 3 ), col=c( 2, 8 ), cex=c( 1, 1 ), ask = TRUE, ... ){
if ( is.R() ) {
d <- dim( x$data$simulated )[[ 2 ]] -1
if ( prod( par( "mfrow" ) ) < d ){
if ( ask ) {
op <- par(ask = TRUE)
on.exit(par(op))
}
}
}
xdat <- x$data$real[, 1 ]
upts <- seq(from =0.001,to=1-0.0001,len=100)
xpts <- revTransform(upts,data=x$data$real[, 1 ], qu = mean(x$data$real[,1] < x$mth[1]), th=x$mth[1],sigma = x$gpd.coef[3,1], xi = x$gpd.coef[4,1])
for( i in 2:( dim( x$data$real )[[ 2 ]] ) ){
ydat <- x$data$real[, i ]
xlimits <- range( xdat , x$data$simulated[ , 1 ] )
ylimits <- range( ydat , x$data$simulated[ , i ] )
plot( xdat , ydat , xlim=xlimits , ylim=ylimits,
xlab = names( x$data$simulated )[ 1 ],
ylab = names( x$data$simulated )[ i ],
type = "n",...
)
points( x$data$simulated[, 1 ] , x$data$simulated[, i ] ,
col=col[ 2 ] , pch=pch[ 2 ], cex=cex[ 2 ] )
points( xdat, ydat , pch=pch[ 1 ], col=col[ 1 ], cex= cex[ 1 ] )
abline( v = x$data$pth, lty=2, col=3 )
ypts <- revTransform(upts,data=x$data$real[, i ], qu = mean(x$data$real[,i] < x$mth[i]), th=x$mth[i],sigma = x$gpd.coef[3,i], xi = x$gpd.coef[4,i])
lines(xpts,ypts,col=3)
}
invisible()
}
test.plot.predict.mex <- function(){
# check reproduce Figure 6 in Heffernan and Tawn
w <- mex(winter,mqu=0.7,penalty="none", wh="NO", dqu=.7, margins="gumbel", constrain=FALSE)
noMod <- bootmex(w)
noPred <- predict(noMod)
par(mfcol=c(2,2))
res <- plot(noPred,main="Fig. 6 Heffernan and Tawn (2004)")
checkEquals(res, NULL, msg="plot.predict.mex: correct execution")
# check for 2-d data
R <- 20
nsim <- 100
wavesurge.mex <- mex(wavesurge,mq=.7,which=1, margins="laplace")
wavesurge.boot <- bootmex(wavesurge.mex,R=R)
wavesurge.pred <- predict(wavesurge.boot,nsim=nsim)
par(mfrow=c(1,1))
res <- plot(wavesurge.pred)
checkEquals(res, NULL, msg="plot.predict.mex: correct execution")
}
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