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# Calculate NPDE from PDE data
# roxygen comments
#' Calculates individual normalized prediction distribution errors (NPDE) from
#' PDE data.
#'
#' \pkg{nca.npde} calculates individual normalized prediction distribution
#' errors (NPDE) of selected NCA metrics from the PDE data.
#'
#' \pkg{nca.npde} calculates individual normalized prediction distribution
#' errors (NPDE) of selected NCA metrics from PDE data. The The deviation of
#' each estimated NCA metrics is scaled by the "spread" of the simulated values.
#' By default, this function calculates the NPDE values of all columns of the
#' input data frame.
#'
#' @param pdedata A data frame containing the prediction distribution errors
#' (PDE) of NCA metrics
#' @param pdecol The range of column numbers in the data frame containing the
#' PDE values, which will be used to calculate the corresponding NPDE
#'
#' @return returns the data frame with the NPDE values based on the input data.
#' @export
#'
nca.npde <- function(pdedata,
pdecol){
"qnorm" <- NULL
rm(list=c("qnorm"))
if (is.null(pdecol)){
pdecol <- names(pdedata)
}else if (!is.null(pdecol) && !is.numeric(pdecol)){
if (!all(pdecol%in%names(pdedata))) stop("All column names given as PDE data column must be present in pdedata")
}else if (!is.null(pdecol) && is.numeric(pdecol)){
if (any(pdecol <= 0) | (max(pdecol) > ncol(pdedata))) stop("Column number for PDE data out of range of pdedata.")
pdecol <- names(pdedata)[pdecol]
}
npde <- pdedata
npde[,pdecol] <- lapply(npde[,pdecol], FUN=function(x) qnorm(as.numeric(x)))
npde[mapply(is.infinite, npde)] <- 0
names(npde)[which(names(npde)%in%pdecol)] <- paste("npde",names(npde)[which(names(npde)%in%pdecol)],sep="")
return(npde)
}
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