Timeline for Variance inhomogeneity in time series when forecasting
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 22 at 6:56 | vote | accept | Skovbaek | ||
| Dec 27, 2018 at 8:02 | comment | added | Skovbaek | Carl: I am aware that a model that only consists of temperature date will not be a great model to predict temperatures in the future. At the moment I am just learning how to use theese tools and methods. | |
| Dec 26, 2018 at 20:18 | history | edited | kjetil b halvorsen♦ | CC BY-SA 4.0 |
added 1 character in body
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| Dec 26, 2018 at 19:12 | comment | added | Richard Hardy | Campbell & Diebold "Weather Forecasting for Weather Derivatives" (2005) deal with this quite successfully with an ARMA-GARCH model. | |
| Dec 26, 2018 at 18:58 | comment | added | Carl | The variability depends on the location (e.g., latitude, longitude, continental vs coast line) as well as the season. In order to decrease the variability of prediction, multiple other factors would need to be incorporated into the model, so the short answer is no for the model being used. | |
| Dec 26, 2018 at 14:01 | answer | added | IrishStat | timeline score: 1 | |
| Dec 26, 2018 at 12:01 | answer | added | chrishmorris | timeline score: 0 | |
| Dec 26, 2018 at 11:55 | review | First posts | |||
| Dec 26, 2018 at 18:59 | |||||
| Dec 26, 2018 at 11:53 | history | asked | Skovbaek | CC BY-SA 4.0 |