Timeline for Diverse questions on ARIMA
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
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| Oct 21, 2016 at 16:03 | comment | added | IrishStat | @Yassir you asked if there was a way to automatically figure out a way to determine the AR MA structure (if there were unusual values or level/.step changes or seasonal pulses or local time trends ) while being sensitive to both changes in parameters and changes in error variance. The answer is yes but it is not in anything that has been recommended here. | |
| Oct 21, 2016 at 14:29 | answer | added | Yassir | timeline score: 1 | |
| Sep 2, 2016 at 16:11 | comment | added | Richard Hardy | Question on software implementations are off topic here. As you ask "is there a way to automate...", I told you that there is and what it is. It is unimportant that it is implemented in R; the important thing is that the idea behind the algorithm is explained in an academic paper that you can read. | |
| Sep 2, 2016 at 15:38 | comment | added | Yassir | Thanks @RichardHardy, but is there any similar method on python or not !! because I do not think that statsmodels on python has something like this. Anyway, could you suggest a way to take the information directly from ACF and PACF matrices and then apply a special analysis to figure out the AR and MA | |
| Sep 2, 2016 at 15:18 | answer | added | Will | timeline score: 0 | |
| Sep 2, 2016 at 15:07 | comment | added | Richard Hardy |
4. auto.arima algorithm by Hyndman and Kandakhar as implemented in "forecast" package in R. See a description in an article in Journal of Statistical Software.
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| Sep 2, 2016 at 15:04 | history | edited | Richard Hardy | CC BY-SA 3.0 |
edited tags
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| Sep 2, 2016 at 14:59 | review | First posts | |||
| Sep 2, 2016 at 15:16 | |||||
| Sep 2, 2016 at 14:57 | history | asked | Yassir | CC BY-SA 3.0 |