Nothing
predP<-function(data, dist, no, n, order=NULL, start=NULL, conf=0.95){
if(!is.numeric(data)|| is.character(data) || is.matrix(data))
stop("data must be a numeric vector")
if(!is.numeric(no)|| is.character(no) || is.matrix(no) )
stop("no must be a numeric vector")
if(!is.numeric(n)|| is.character(n) || is.matrix(n) )
stop("n must be a numeric vector")
distname<- dist
ld<-length(data)
ls<-no+ld
if(ls > n ){stop("number of observations exceeds n")}
if( ld >= n) { stop("n must be greater than data length")}
if (is.element(distname, c("exp", "norm", "lnorm", "gamma", "logis", "weibull", "unif"))){
for(k in (ld+1):ls){
s<-k
PI<-predI(data, distname, s, n, conf=conf)
l<-PI$lower
u<-PI$upper
xnew<- (l+u)/2
data<-c(data,xnew)}
}
else{
if(is.null(order)){
stop("moment matching estimation needs an 'order' argument")}
else {
for(k in (ld+1):ls){
s<-k
PI<-predI(data, distname, s, n, order=order, start=start, conf=conf)
l<-PI$lower
u<-PI$upper
xnew<- (l+u)/2
data<-c(data,xnew)}
}
}
ns<- (ld+1):ls
newobs<- data[ns]
results <-list(data=data, newobs=newobs , ns=ns , no=no , distname=distname , ld=ld , n=n)
return(structure(results, class = "predP"))
}
print.predP <- function(x,...) {
if (!inherits(x, "predP"))
stop("Use only with 'predP' objects")
cat("Prediction points for future observations based on '", x$distname, "' distribution \n")
cat("Prediction points:\n")
print(cbind.data.frame("s" = x$ns, "xs" = x$newobs), ...)
}
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