Timeline for How to model and generate forecasts for time series with missing observations? [duplicate]
Current License: CC BY-SA 3.0
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| Jul 21, 2019 at 11:42 | history | edited | kjetil b halvorsen♦ |
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| Mar 23, 2017 at 18:08 | history | closed |
Aksakal kjetil b halvorsen♦ gung - Reinstate Monica r Users with the r badge or a synonym can single-handedly close r questions as duplicates and reopen them as needed. |
Duplicate of Is there any gold standard for modeling irregularly spaced time series? | |
| Mar 23, 2017 at 17:53 | comment | added | Chris Haug | Alternatively, you may be able to consider it a regularly-spaced time series with missing values. In that case, any state-space model which can be estimated through the Kalman filter algorithm will work automatically with missing values, and the algorithm will also provide non-anticipating estimates for the missing values, and forecasts. | |
| Mar 23, 2017 at 17:53 | review | Close votes | |||
| Mar 23, 2017 at 18:08 | |||||
| Mar 23, 2017 at 17:34 | history | edited | Chill2Macht | CC BY-SA 3.0 |
deleted 58 characters in body; edited title
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| Mar 23, 2017 at 16:43 | answer | added | DaBenski | timeline score: 1 | |
| Mar 23, 2017 at 15:28 | history | asked | Paul | CC BY-SA 3.0 |