rfPredict <- function(test, history, nDays){
## 'test' contains only the predictor set
## 'history' contains the predictor set and the output variable in the first column
n <- as.character(nDays)
switch(n,
'0'={
train <- history[which(!(index(history) %in% index(test))),]
},
'all'={
train <- history
},{
d <- unique(as.Date(index(test)))[1]
train <- window(history,
start = as.POSIXct(d-nDays)+3600,
end = as.POSIXct(d))
})
qrfModelH <- quantregForest(train[,-1], as.numeric(train[,1]))
qrfPredH <- predict(qrfModelH, test)
colnames(qrfPredH) <- c('q1', 'q5', 'q9')
qrfPredH <- zoo(qrfPredH, index(test))
}
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