Timeline for Model/explain a time series as a function of other time series - R
Current License: CC BY-SA 3.0
12 events
| when toggle format | what | by | license | comment | |
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| Jun 29, 2016 at 20:46 | comment | added | stem | @horaceT no intertemporal dependence is required, only contemporaneous relations | |
| Jun 28, 2016 at 20:34 | answer | added | horaceT | timeline score: 4 | |
| Jun 28, 2016 at 18:48 | comment | added | horaceT | @stem Do you just want contemporaneous relationship, or intertemporal dependence, ie. $x^1_t = f( x^2_t, x^2_{t-1}, ...., x^3_t, x^3_{t-1},...., x^6_t, x^6_{t-1}....)$ | |
| Jun 27, 2016 at 14:51 | comment | added | stem | @Roland my aim is to understand how each time series influences ts1, and use those that have most of the influence on ts1 for predictions. I'd say my goal is dimensionality reduction and prediction | |
| Jun 27, 2016 at 14:48 | answer | added | shadowtalker | timeline score: 4 | |
| Jun 27, 2016 at 14:40 | comment | added | Roland | What is your goal? Inference, prediction, or forecast? R package nlme offers regression models that include a model for residual autocorrelation. | |
| Jun 27, 2016 at 14:23 | history | edited | stem | CC BY-SA 3.0 |
added specification: R
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| Jun 27, 2016 at 13:44 | answer | added | Tom Reilly | timeline score: 4 | |
| S Jun 27, 2016 at 13:20 | history | suggested | Mud Warrior | CC BY-SA 3.0 |
Fixed grammar and improved formatting
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| Jun 27, 2016 at 12:57 | review | Suggested edits | |||
| S Jun 27, 2016 at 13:20 | |||||
| Jun 27, 2016 at 12:39 | review | First posts | |||
| Jun 27, 2016 at 12:41 | |||||
| Jun 27, 2016 at 12:39 | history | asked | stem | CC BY-SA 3.0 |