R/cdf.ensembleMOScsg0.R

In ensembleMOS: Ensemble Model Output Statistics

cdf.ensembleMOScsg0 <-
function(fit, ensembleData, values, dates = NULL, randomizeATzero = FALSE, ...)
{

 matchITandFH(fit,ensembleData)

 M <- matchEnsembleMembers(fit,ensembleData)
 nForecasts <- ensembleSize(ensembleData)
 if (!all(M == 1:nForecasts)) ensembleData <- ensembleData[,M]

## remove instances missing all forecasts

 M <- apply(ensembleForecasts(ensembleData), 1, function(z) all(is.na(z)))
 ensembleData <- ensembleData[!M,]

## match specified dates with dateTable in fit

 dateTable <- dimnames(fit$B)[[2]]

 if (!is.null(dates)) {

   dates <- sort(unique(as.character(dates)))

   if (length(dates) > length(dateTable))
     stop("parameters not available for some dates")

   K <- match( dates, dateTable, nomatch=0)

   if (any(!K) || !length(K))
     stop("parameters not available for some dates")

 }
 else {

   dates <- dateTable
   K <- 1:length(dateTable)

  }

 ensDates <- ensembleValidDates(ensembleData)

## match dates in data with dateTable
 if (is.null(ensDates) || all(is.na(ensDates))) {
   if (length(dates) > 1) stop("date ambiguity")
   nObs <- nrow(ensembleData)
   Dates <- rep( dates, nObs)
 }
 else {
## remove instances missing dates
   if (any(M <- is.na(ensDates))) {
     ensembleData <- ensembleData[!M,]
     ensDates <- ensembleValidDates(ensembleData)
   }
   Dates <- as.character(ensDates)
   L <- as.logical(match( Dates, dates, nomatch=0))
   if (all(!L) || !length(L))
     stop("model fit dates incompatible with ensemble data")
   Dates <- Dates[L]
   ensembleData <- ensembleData[L,]
   nObs <- length(Dates)
 }

 nForecasts <- ensembleSize(ensembleData)
 nVal <- length(values)

 CDF <- matrix(NA, nObs, nVal)
 dimnames(CDF) <- list(ensembleObsLabels(ensembleData),
                          as.character(values))

 ensembleData <- ensembleForecasts(ensembleData)

 l <- 0
 for (d in dates) {

    l <- l + 1
    k <- K[l]

    B <- fit$B[,k]
    if (all(Bmiss <- is.na(B))) next
    A <- fit$a[,k]
    C <- fit$c[,k]
    D <- fit$d[,k]
    Q <- fit$q[,k]

    I <- which(as.logical(match(Dates, d, nomatch = 0)))

    for (i in I) {
        f <- ensembleData[i,]
        S.sq <- mean(f)
        f <- c(1,f)
        Mu <- c(A,B)%*%f  #mean of gamma
        Sig.sq <- C + D*S.sq #variance of gamma
        
        Shp <- Mu^2/Sig.sq  #shape of gamma
	      Scl <- Sig.sq/Mu    #scale of gamma
        
	      if (randomizeATzero){
	        cdfval <- pgamma(values+Q, shape = Shp, scale = Scl)* (values>=0)
	        zeroval <- runif(nVal,min=rep(0,nVal),max=cdfval)
	        
	        CDF[i,] <- cdfval * (values>0)+ zeroval * (values==0)
	      } else {
	        CDF[i,] <- pgamma(values+Q, shape = Shp, scale = Scl)* (values>=0)
	      }
        
    }
 }

 if (any(is.na(CDF))) warning("NAs in cdf values") 
 CDF
}