theDataSet=AirPassengers
frequency(theDataSet)
horizon=2*frequency(theDataSet)
train=theDataSet[1:(length(theDataSet)-horizon)] #forecast the last horizon of the series
actuals=theDataSet[(length(theDataSet)+1-horizon):length(theDataSet)]
reg.data = matrix(rnorm(length(theDataSet)))
reg.train = reg.data[1:(length(theDataSet)-horizon)]
reg.test = reg.data[(length(theDataSet)+1-horizon):length(theDataSet)]
rstanmodel = rlgt(train,
seasonality=frequency(theDataSet),
level.method="seasAvg",
xreg = reg.train,
control=rlgt.control(NUM_OF_ITER=10000))
forec = forecast(rstanmodel, reg.test, h = 24)
Error in regFittedS[(length(regFittedS) - seasonality_int + 1):length(regFittedS)] :
only 0's may be mixed with negative subscripts
theDataSet=AirPassengers
frequency(theDataSet)
horizon=2*frequency(theDataSet)
train=theDataSet[1:(length(theDataSet)-horizon)] #forecast the last horizon of the series
actuals=theDataSet[(length(theDataSet)+1-horizon):length(theDataSet)]
reg.data = matrix(rnorm(length(theDataSet)))
reg.train = reg.data[1:(length(theDataSet)-horizon)]
reg.test = reg.data[(length(theDataSet)+1-horizon):length(theDataSet)]
rstanmodel = rlgt(train,
seasonality=frequency(theDataSet),
level.method="seasAvg",
xreg = reg.train,
control=rlgt.control(NUM_OF_ITER=10000))
forec = forecast(rstanmodel, reg.test, h = 24)
Error in regFittedS[(length(regFittedS) - seasonality_int + 1):length(regFittedS)] :
only 0's may be mixed with negative subscripts