Hello,

I wanted to check the forecast data by using training and test method using random walk with drift method. however i received an error

###########Splitting data into training and test data sets############

TS_Train <- window(FCL_forecasttimeseries, start=c(2012,14), end=c(2017,24), freq=24)

TS_Test <- window(FCL_forecasttimeseries, start=c(2018,1), freq=24)

TS_Train

TS_Test

autoplot(TS_Train, series = "Train")+ autolayer(TS_Test, series = "Test") + ggtitle("FCL rates Training & Test data") + xlab("periods")+ylab("Rates")+ guides(colour=guide_legend(title = "Forecast"))

#############FORECASTING MAEHODS ############

###########R1.Random walk with drift forecasting (using Log value) for Test & Training data#########

fit_decomposelog <- stl(log10(TS_Train), s.window = "p")

fit_decomposelog

TS_Train_stl <- forecast(fit_decomposelog, method = "rwdrift", h=36) ##### (h=36)No. of periods that you want to forecast######

plot(TS_Train_stl)

TS_Train_stl

########Accuracy measures: RMSE and MAPE using RWD#########

vec2 <- 10^(cbind(log10(TS_Test), as.data.frame(forecast(fit_decomposelog, method = "rwdrift", h=36)[,1])))

the error states:

Error in forecast(fit_decomposelog, method = "rwdrift", h = 36)[, 1] :

incorrect number of dimensions

Can you please help me with this

thank you

Sachin