4 Replies Latest reply: May 25, 2016 6:10 AM by Ashvin Ramiah RSS

    QlikSense - R with Arima Prediction


      I have a customer with the sample attached data.
      Who wants me to display predictive values for next one year.


      Can anyone of you, show me or send me the Required R codes required to generate the futuristic data for Next one year based on the sample file:

      Activity Period : is my Field for Period
      Passenger Count: is my field for values.


      I have downloaded R-studio.

      But not understanding the concept of Ts, arima etc.

      If someone can explain to me.. that will be very much appreciated . My Skpye id: ashvinzoe


      At the end, i want to use the predicted data to display in a graph.

      ( from qlikview i know we have linear prediction, however Customer wants an ideal forecast graph )








        • Re: QlikSense - R with Arima Prediction
          Boopesh Jayabalaji

          Hi Ashvin,


          I went through your dataset. May i understand at what level you would want to predict the data.




            • Re: QlikSense - R with Arima Prediction

              For instance the last period was : 200606

              And what is required is to predict till 200706.


              I have managed to use grouping to get the Period per month.


              > csvdata <- read.csv("MonthlyPassengerData_200507_to_201509.csv", header = TRUE)

              > xPeriod  <- csvdata[1]

              > yPax <- csvdata["Passenger.Count"]

              > df = data.frame(xPeriod,yPax);


              // use library(data.table)

              dfSummarize <-  aggregate(Passenger.Count ~ Activity.Period, df, sum)


              Activity.Period   total

                           (int)   (int)

              1           200507 3225769

              2           200508 3195866

              3           200509 2740553

              4           200510 2770715

              5           200511 2617333

              etc etc



              Convert date from YYYYMM to YYYY-MM-DD

              // where initialy dfSummarize[[1]] has a list of date in YYYYMM

              dfSummarize[[1]] <-  as.Date(paste(dfSummarize[[1]],"01", sep = ""), format = "%Y%m%d")


              So from here... i need to get next 12 months data...

                • Re: QlikSense - R with Arima Prediction

                  Ok guy, i gat it working.


                  // This is going to generate all the difference between the present and past row of data.

                  // Remember to send the DAta Measure into that. NEVER THE DATE.

                  // lag = 1 ::  diference between 2 rows immediate

                  // lag = 1  :: difference bewen Two 2 rows... behind.

                  dif1 = diff(dfSummarize[[2]] , lag = 1  )  



                  // When plot of you will know whether it is stationary or not.




                  // UNTIL you get a staiotnay plot... u need to keep on Differentioating...

                  // remember... you need to Diff the diff ...



                  // Check these tw0 ONLY WHEN YOU HAEV A STATIONARY SERIES.. u can use these fucntion.

                  // numbe rof AR terms

                  pacf(dif1) // from this chart >> locate the PEEK. The highest. VALUE ABOVE THE BLUE LINE. Max line out of the RANGE ( Blue dotted lines)

                  // numbe rof  MA terms

                  acf(dif1)  // from this chart >> locate the PEEK. The highest.



                  // calculate the Fit

                  c(6,1,6) = 1 here is the number of Diff we have made. No of times we have differentiate to be stationary.



                  fit  <- arima(x = dfSummarize[[2]] , order = c(6,1,6)  )

                  fit  <- arima(x = dfSummarize[[2]] , order = c(6,1,6)  )

                  fit  <- arima(x = dfSummarize[[2]] , order = c(12,1,12))

                  fit  <- arima(x = dfSummarize[[2]] , order = c(6,1,6)  )



                  // WHY DONT U reduce the amount of data loaded and then when predict, do the prediction for KNOWN values.

                  // u will know whether the model is best fit.

                  // VALIDATION of Forecast data.





                  // Finally forcast .... H = 12.. depends on what you want to predict.. periods... how many values.

                  pForecast <- forecast(fit, h = 12)

              • Re: QlikSense - R with Arima Prediction
                Sangram Reddy

                Hi Ashvin,


                This link here will give you more information on how to implement ARIMA.



                Also, once done with your predictive model , you can plot the data in Qliksense in a line chart as I have done in my project (I made use of random forest time series forecasting).

                You can color the line chart the way you need. Please check the image below: the red and the yellow lines are the confidence bands.Line chart(1).PNG