Timeline for Learning the raw mathematics behind VAR modelling to implement it myself
Current License: CC BY-SA 3.0
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| Feb 18, 2020 at 23:59 | answer | added | kjetil b halvorsen♦ | timeline score: 0 | |
| Sep 2, 2018 at 13:39 | history | edited | kjetil b halvorsen♦ |
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| Mar 27, 2018 at 7:29 | history | edited | Richard Hardy | CC BY-SA 3.0 |
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| Mar 27, 2018 at 7:27 | comment | added | Richard Hardy |
The way the vars package estimates VAR models is equation-by-equation. For that, knowing simple regression is enough (which may be surprising). You do not need to learn ARIMA because (1) it is not a subset of VAR and (2) it involves different logic and different estimation techniques which are much more difficult to implement it in practice.
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| Mar 27, 2018 at 0:33 | comment | added | Graeme Walsh | This could prove tricky. For example, James Gentle in his book Computational Statistics says that statisticians should be aware that "the form of mathematical expression and the way the expression should be evaluated in practice may be quite different". For that reason, time-series books may be only useful to a certain degree. You will also need some decent linear algebra / computational statistics references to complete this admirable objective. I'd say, it's a lot of work and you'll need to understand a lot - more than time-series. | |
| Mar 26, 2018 at 23:17 | comment | added | dimitriy | Maybe also Applied Econometric Time Series by Walter Enders. | |
| Mar 26, 2018 at 23:12 | comment | added | dimitriy | Have you considered Introduction to Multiple Time Series Analysis by Helmut Lütkepohl and Time Series Analysis by James D. Hamilton? | |
| Mar 26, 2018 at 22:40 | history | asked | w0f | CC BY-SA 3.0 |