Multivariate ARIMA (MARIMA) modelling in R










0














I am currently using the Marima package for R invented by Henrik Spliid in order to forecast multivariate time series with ARIMA.
Overview can be found here:



https://cran.r-project.org/web/packages/marima/marima.pdf
http://orbit.dtu.dk/files/123996117/marima.anv.talk.pdf



When using the Marima function, it is required to define both the order of AR(p) and MA(q) first.



My question is, how can I determine appropriate values for p and q?



I know when it comes to univariate ARIMA analysis, that auto.arima gives a good suggestion for p and q. However, when I use auto.arima for every single univariate time series I want to analyze, there are (slightly) different suggestions for each time series. (For example (2,2,1) for the first, (1,1,1) for the second and so on)



Since I want to analyze all of the time series combined in the multivariate ARIMA model and I only can choose one value for each p and q (if I understood it correctly), I wonder how I can choose those values the most accurate way.



Could I just try to run the model a couple times and see what values for p and q work best (e.g. by testing the residuals of the forecast)?



What are your suggestions?



I would appreciate any help!










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  • I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
    – 42-
    Nov 13 '18 at 7:18
















0














I am currently using the Marima package for R invented by Henrik Spliid in order to forecast multivariate time series with ARIMA.
Overview can be found here:



https://cran.r-project.org/web/packages/marima/marima.pdf
http://orbit.dtu.dk/files/123996117/marima.anv.talk.pdf



When using the Marima function, it is required to define both the order of AR(p) and MA(q) first.



My question is, how can I determine appropriate values for p and q?



I know when it comes to univariate ARIMA analysis, that auto.arima gives a good suggestion for p and q. However, when I use auto.arima for every single univariate time series I want to analyze, there are (slightly) different suggestions for each time series. (For example (2,2,1) for the first, (1,1,1) for the second and so on)



Since I want to analyze all of the time series combined in the multivariate ARIMA model and I only can choose one value for each p and q (if I understood it correctly), I wonder how I can choose those values the most accurate way.



Could I just try to run the model a couple times and see what values for p and q work best (e.g. by testing the residuals of the forecast)?



What are your suggestions?



I would appreciate any help!










share|improve this question





















  • I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
    – 42-
    Nov 13 '18 at 7:18














0












0








0







I am currently using the Marima package for R invented by Henrik Spliid in order to forecast multivariate time series with ARIMA.
Overview can be found here:



https://cran.r-project.org/web/packages/marima/marima.pdf
http://orbit.dtu.dk/files/123996117/marima.anv.talk.pdf



When using the Marima function, it is required to define both the order of AR(p) and MA(q) first.



My question is, how can I determine appropriate values for p and q?



I know when it comes to univariate ARIMA analysis, that auto.arima gives a good suggestion for p and q. However, when I use auto.arima for every single univariate time series I want to analyze, there are (slightly) different suggestions for each time series. (For example (2,2,1) for the first, (1,1,1) for the second and so on)



Since I want to analyze all of the time series combined in the multivariate ARIMA model and I only can choose one value for each p and q (if I understood it correctly), I wonder how I can choose those values the most accurate way.



Could I just try to run the model a couple times and see what values for p and q work best (e.g. by testing the residuals of the forecast)?



What are your suggestions?



I would appreciate any help!










share|improve this question













I am currently using the Marima package for R invented by Henrik Spliid in order to forecast multivariate time series with ARIMA.
Overview can be found here:



https://cran.r-project.org/web/packages/marima/marima.pdf
http://orbit.dtu.dk/files/123996117/marima.anv.talk.pdf



When using the Marima function, it is required to define both the order of AR(p) and MA(q) first.



My question is, how can I determine appropriate values for p and q?



I know when it comes to univariate ARIMA analysis, that auto.arima gives a good suggestion for p and q. However, when I use auto.arima for every single univariate time series I want to analyze, there are (slightly) different suggestions for each time series. (For example (2,2,1) for the first, (1,1,1) for the second and so on)



Since I want to analyze all of the time series combined in the multivariate ARIMA model and I only can choose one value for each p and q (if I understood it correctly), I wonder how I can choose those values the most accurate way.



Could I just try to run the model a couple times and see what values for p and q work best (e.g. by testing the residuals of the forecast)?



What are your suggestions?



I would appreciate any help!







r time-series arima






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asked Nov 13 '18 at 3:15









Federico Filter

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  • I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
    – 42-
    Nov 13 '18 at 7:18

















  • I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
    – 42-
    Nov 13 '18 at 7:18
















I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
– 42-
Nov 13 '18 at 7:18





I suggest raising a flag to migrate to CrossValidated.com, although it would be quicker to copy this to a temp document, delete the question here and thenn post on CV. They handle methods questions. We handle question where you know what to do.
– 42-
Nov 13 '18 at 7:18













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