Timeline for Does backcasting work the same way as forecasting?
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| Apr 23, 2021 at 16:10 | comment | added | zbicyclist | Yes, the autocorrelation between the two variables. Variable 1 is the unlagged series, Variable 2 is he lagged series. | |
| Apr 23, 2021 at 13:14 | comment | added | user107224 | @zbicyclist I thought particularly get this. When you talk about correlation between variables are you referring to the autocorrelation between two points on the series? | |
| Apr 23, 2021 at 8:26 | history | edited | user107224 | CC BY-SA 4.0 |
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| Apr 22, 2021 at 22:46 | history | edited | user107224 | CC BY-SA 4.0 |
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| Apr 22, 2021 at 18:00 | history | tweeted | twitter.com/StackStats/status/1385292374566445059 | ||
| Apr 22, 2021 at 12:42 | comment | added | zbicyclist | It works because the correlation of variable 1 with variable 2 is the same as the correlation of variable 2 with variable 1. It may be easier not to think of this as time, but as distance, which is clearly reversible, e.g. the correlation of temperature of two points a mile apart is the same no matter which direction you are considering. | |
| Apr 22, 2021 at 12:34 | comment | added | user107224 | @RobHyndman hi thanks for the reply. Why does this work though? For example, with a normal model, we have $X_{t+1}=f(X_t)$, which makes sense since we are conditioning on past information, but with backcasting, $X_t=f(X_{t+1})$ which means conditioning on the future? | |
| Apr 22, 2021 at 9:54 | history | edited | user107224 | CC BY-SA 4.0 |
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| Apr 22, 2021 at 5:20 | comment | added | Rob Hyndman | See otexts.com/fpp3/backcasting.html | |
| Apr 22, 2021 at 2:51 | history | asked | user107224 | CC BY-SA 4.0 |