#' @title perMdPrediction
#'
#' @description This function is to caltulate rmse.
#'
#' @param mPath : Basic path of the models
#'
#' @param mFiles: Files names of the models
#'
#' @param mids:A vector of the models index
#'
#' @param mF: Starting index of the models to be used to make the prediction
#'
#' @param mT: Ending index of the models to be used to make the prediction
#'
#' @param bnd: BND format of polygons for spatial effect modeling
#'
#' @param dset: New data frame to be predicted
#'
#' @param outPath: The path to save the files of the predicted results.
#'
#' @param idF: Field name of id
#'
#' @param ridF: Field name of the regional id
#'
#' @return NULL. All the predicted values saved int the appointed path.
#'
#' @export perMdPrediction
#'
perMdPrediction=function(mPath,mFiles,mids,mF,mT,bnd,dset,outPath,idF,ridF){
assign("bnd",bnd)
for(i in c(mF:mT)){
model=readRDS(paste(mPath,"/",mFiles[i],sep=""))
dset$pre=exp(predict(model,dset))
cols=c(idF,ridF,"pre")
outFl=paste(outPath,"/m_",mids[i],".csv",sep="")
write.csv(dset[,cols],file=outFl,row.names=FALSE)
rm(list=c("index","outFl","model"))
gc()
}
return(0)
}
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