Build own function for forecasting

Question

I have one data frame, which is composed of three columns(PIT,CIT and VAT). My intention is to make forecast with each of this three times series with Forecast package. For that reason I convert data frame into ts object.

Now I want to make forecasting with snaive function which is part from Forecast package.So I wrote this lines of code:

  SNAIVE_PIT<-snaive(TS_REVENUES[, 'PIT'],h=5) 
  SNAIVE_CIT<-snaive(TS_REVENUES[, 'CIT'],h=5) 
  SNAIVE_VAT<-snaive(TS_REVENUES[, 'VAT'],h=5)

But my intention is to simplify this code with some function like: loop,for or other function, which can automatically calculate forecasting for each of this three times series(PIT,CIT and VAT) ? I am asking this because this time series is only small part of whole series and I must to simplify this forecasting procedures.

#CODE

library(forecast)

  # Making data frame 
   DATA_SET<-data.frame(
                    PIT=seq(1, 48, by = 2),
                    CIT=seq(1, 24, by = 1),
                    VAT=seq(1, 94, by = 4)
                    )
     View(DATA_SET)

    # Making TS object
      TS_REVENUES<-ts(DATA_SET,start=c(2016,1),frequency = 12)

    # Extracting column names from TS object
      COL_NAMES_TS<-TS_REVENUES[0:0,]
      COL_NAMES_TS

    # Making forecasting with Forecast package      
      SNAIVE_PIT<-snaive(TS_REVENUES[, 'PIT'],h=5) 
      SNAIVE_CIT<-snaive(TS_REVENUES[, 'CIT'],h=5) 
      SNAIVE_VAT<-snaive(TS_REVENUES[, 'VAT'],h=5)

olorcain · Accepted Answer · 2019-04-17 10:26:31Z

1

If I understand you correctly, then you want to cycle through each column in your dataframe and forecast from it. If so, I think the code below will help.

library(forecast)

# Making data frame 
DATA_SET<-data.frame(
  PIT=seq(1, 48, by = 2),
  CIT=seq(1, 24, by = 1),
  VAT=seq(1, 94, by = 4)
)
View(DATA_SET)

for(i in 1:ncol(DATA_SET)){
  # Build a ts for this column
  timeseries <- ts(DATA_SET[,i], start=c(2016,1), frequency = 12)
  # Build a foreacst based on the ts
  forecast <- snaive(timeseries,h=5)

  # rename the forecast according to the original variable name
  colname <- colnames(DATA_SET)[i]
  forecastName <- paste("SNAIVE_",colname," <- forecast",sep="")
  eval(parse(text = forecastName))
}

answered Apr 17, 2019 at 10:26

olorcain

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