Timeline for How to determine Forecastability of time series?
Current License: CC BY-SA 3.0
17 events
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| Jul 18, 2016 at 15:38 | vote | accept | forecaster | ||
| Jul 5, 2016 at 13:19 | comment | added | Sean Easter | My sense is that this is a much narrower question than the suggested duplicate. Voting leave open, but suggest the OP consider a more specific title to avoid confusing the two. Say, "How to determine forecastability of times series using approximate entropy?" | |
| Jul 5, 2016 at 10:12 | review | Close votes | |||
| Jul 5, 2016 at 14:24 | |||||
| Jul 5, 2016 at 9:55 | comment | added | Tim | Possible duplicate of Assessing forecastability of time series | |
| Jul 5, 2016 at 9:48 | history | edited | Tim |
edited tags
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| S Aug 12, 2015 at 7:07 | history | suggested | Dawny33 | CC BY-SA 3.0 |
Removed unnecessary text.
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| Aug 12, 2015 at 6:19 | review | Suggested edits | |||
| S Aug 12, 2015 at 7:07 | |||||
| S Aug 12, 2015 at 6:12 | history | suggested | Dawny33 | CC BY-SA 3.0 |
improved formatting for better understanding.
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| Aug 12, 2015 at 5:47 | answer | added | Hidden Markov Model | timeline score: 0 | |
| Aug 12, 2015 at 5:39 | review | Suggested edits | |||
| S Aug 12, 2015 at 6:12 | |||||
| Jan 20, 2015 at 2:06 | comment | added | Aksakal | Sure, univariate forecasting has its uses. It's just in my domain it's rarely useful. In my case it's either I have to forecast multiple correlated endogenous series, or my series are clearly correlated with exogenous factors. | |
| Jan 20, 2015 at 0:26 | comment | added | forecaster | @Aksakal, no there is no explanatory variables. I was looking for large scale univariate (no explanatory variable) time series forecasting where we need an objective measure to assess forecastability. Also, in many many instances, univariate forecasting is much more accurate than models built with explanotary variables. | |
| Jan 19, 2015 at 23:56 | answer | added | Aleksandr Blekh | timeline score: 8 | |
| Jan 19, 2015 at 22:06 | comment | added | Aksakal | Does it account for explanatory variables? For instance, if you're forecasting account attrition of a firm, it may be correlated with marketing spending, and spending is highly forecastable, in fact, it's planned months ahead. How would this be accounted in the proposed approach? | |
| Jan 19, 2015 at 21:47 | comment | added | user66962 | As stated in the article approximate entropy should not be used on short time series, N<200. More importantly, the article uses sample entropy not approximate entropy. Pracma contains both. Thanks | |
| Dec 5, 2014 at 22:32 | history | edited | forecaster | CC BY-SA 3.0 |
edited title
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| Dec 5, 2014 at 22:17 | history | asked | forecaster | CC BY-SA 3.0 |