How Forecast a time series with CART models

Question

I'm using the rpart library from R to try forecasting the electricity consumption from Australia (example from the book Introductory Time Series with R):

library(rpart)
www <- "http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/cbe.dat"
CBE <- read.table(www, header = T)
Elec.ts <- ts(CBE[, 3], start = 1958, freq = 12)

plot(cbind(Elec.ts))


fit <- rpart(elec~elec, method="anova", data=CBE)
pre <- predict(fit)

Elec.predict <- ts(pre[], start = 1958, freq = 12)
plot(cbind(Elec.ts,Elec.predict ))

It's really simple, the R program does not run , if I try to create a model using the elec data it self .

Am I using it wrong?
How Can I use this library properly ?

Answer 1

Solving the problem with this script.

I have created a github site with all informations about the script and the time series data. http://alvarojoao.github.io/timeseriesExamples

library(caret)
library(ggplot2)
library(pls)
library(data.table)
library(rpart)
library(bst)
library(plyr)

nLag <- 12
khorizon <- 1

www <- "./databases/elec.dat"
CBE <- read.table(www, header = T)
base <- CBE
variable <- 'elec'
base$elec = (base$elec-min(base$elec))/(max(base$elec)-min(base$elec))

base <- setDT(base)[, paste0(variable, 1:nLag) := shift(elec, 1:nLag)][]
base <- base[(nLag+1):nrow(base),]

Elec.ts <- ts(CBE[, 1], start = 1958, freq = 12)
acf(CBE$elec)
plot(cbind(Elec.ts))



timeSlices <- createTimeSlices(1:nrow(base), 
                   initialWindow =nrow(base)*2/3, horizon = khorizon , fixedWindow = FALSE)
str(timeSlices,max.level = 1)
trainSlices <- timeSlices[[1]]
testSlices <- timeSlices[[2]]
predTest  <- c(1,2)
predTest  <- predTest[0]
trueTest  <- c(1,2)
trueTest  <- trueTest[0]

for(i in 1:length(trainSlices)){

  plsFitTime <- train(elec ~  .,
                      data = base[trainSlices[[i]],], 
                      method = "treebag"
                      )



  pred <- predict(plsFitTime,base[testSlices[[i]],])


  true <- base$elec[testSlices[[i]]]
}