Timeline for Goodness of forecast in R (Time Series)
Current License: CC BY-SA 3.0
5 events
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| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
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| Sep 30, 2015 at 6:07 | comment | added | Richard Hardy |
$p$-value has nothing to do with forecast accuracy, at least directly. Thus when interested in forecast accuracy, just look at the output of the accuracy function. That points to model 2 being preferred to model 1. However, I share your concern about the mean error. Ideally, ME indeed should be close to zero. If your observations are not measured in billions or so, the current ME looks poor. Maybe you are trying to fit the model to a data that clearly cannot be described by this kind of model?..
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| Sep 30, 2015 at 5:24 | vote | accept | Ashish Anand | ||
| Sep 29, 2015 at 4:55 | comment | added | Ashish Anand | Taking into account just the accuracy of the forecast : 1. Model 1 has higher p-value and Model 2 has lower values for MASE etc. Which out of the two can is say is a better prediction? 2. For any forecast, is it not like ME(mean of errors) should be close to 0. Here I am seeing 424 and 284. | |
| Sep 28, 2015 at 20:23 | history | answered | Richard Hardy | CC BY-SA 3.0 |