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#' @rdname predict.evmOpt
#' @export
plot.lp.evmOpt <- function(x, main=NULL,
pch= 1, ptcol =2 , cex=.75, linecol = 4 ,
cicol = 1, polycol = 15, plot.=TRUE, ...){
x <- x$obj
family <- x$family
x <- x$link
if(dim(x)[1] == 1){
stop("Need range of covariate values to plot linear predictors")
}
if(length(colnames(x)) <= (length(family$param) + 1) ){
stop("Please use ci.fit=TRUE in call to predict, to calculate confidence intervals")
}
makelp <- function(x, family){
p <- names(family$param)
res <- vector("list", length=length(p))
names(res) <- p
for (i in 1:length(p)){
res[[i]] <- as.matrix(x[, paste0(p[i], c("", ".lo", ".hi"))])
}
res
}
Ests <- makelp(data.frame(x), family)
Names <- names(family$param)
cn <- colnames(x)
ParNames <- paste(rep(Names,each=4),c("",".lo",".hi",".se"),sep="")
which <- ! (cn %in% ParNames)
X <- x[,which]
if(is.null(dim(X))){
X <- matrix(X)
dimnames(X) <- list(dimnames(x)[[1]],dimnames(x)[[2]][which])
}
nPar <- length(Names)
Output <- list(NULL)
nPlot <- 0
for(i in 1:nPar){
for(j in 1:dim(X)[2]){
if(length(unique(Ests[[i]][,1])) > 1){
if(length(unique(X[,j])) > 1){
ord <- order(X[,j])
x <- X[ord,j]
y <- Ests[[i]][ord,]
nPlot <- nPlot + 1
Output[[nPlot]] <- list(x=x,y=y,CovName = colnames(X)[i],ParName = Names[i])
if(plot.){
plot(x, y[,1],type="n",ylab=Names[i],xlab=colnames(X)[j],main=main,ylim=range(y))
if (polycol != 0){
polygon(c( x, rev(x)),
c(y[,2],rev(y[,3])),
col=polycol, border = FALSE) # Close polygon
} else {
lines(x, y[,2], col = cicol)
lines(x, y[,3], col = cicol)
}
lines(x, y[,1], col = linecol[ 1 ] )
}
}
}
}
}
invisible(Output)
}
#' @export
plot.lp.evmSim <- function(x, type="median", plot.=TRUE,...){
if(dim(x$obj$link)[1] == 1){
stop("Need range of covariate values to plot linear predictors")
}
p <- names(x$obj$family$param)
np <- length(p)
# re-format to same column structure as lp.evmOpt x
ColIndexMeans <- 1+4*(0:(np-1))
if(casefold(type) == "median"){
offset <- 1
} else if(casefold(type) == "mean") {
offset <- 0
} else {
stop("type must be \"mean\" or \"median\" ")
}
which <- c(ColIndexMeans + offset,rep(1:2,np) + rep(ColIndexMeans+1,each=2), (4*np+1): dim(x$obj$link)[2])
x$obj$link <- x$obj$link[,which]
colnames(x$obj$link)[1:(3*np)] <- c(p,paste(rep(p,each=2),rep(c(".lo",".hi"),np),sep=""))
plot.lp.evmOpt(x,plot.=plot.,...)
}
#' @export
plot.lp.evmBoot <- plot.lp.evmSim
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