Timeline for R-squared and fit of the model
Current License: CC BY-SA 3.0
17 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 26, 2016 at 13:16 | history | edited | Nick Cox |
edited tags
|
|
| Jan 26, 2016 at 12:23 | vote | accept | Bear | ||
| Jan 26, 2016 at 12:23 | vote | accept | Bear | ||
| Jan 26, 2016 at 12:23 | |||||
| Jan 26, 2016 at 12:07 | answer | added | Nick Cox | timeline score: 1 | |
| Jan 25, 2016 at 22:31 | answer | added | Flounderer | timeline score: 1 | |
| Jan 25, 2016 at 22:05 | comment | added | Bear | Thank you. I'll read it. I've made quantile regression analysis so far. Can you be so kind to look through my post about it and maybe answer some of my questions? stats.stackexchange.com/questions/192464/fit-quantile-regresion | |
| Jan 25, 2016 at 21:40 | comment | added | Nick Cox | I'd consider pulling in the tails to see if there is any structure to consider. Some of those outliers could be messing things up. A cube root transformation is a non-standard possibility. stats.stackexchange.com/questions/179871/… stats.stackexchange.com/questions/85687/… | |
| Jan 25, 2016 at 20:18 | comment | added | Bear | Can you say something about A itself? I've made a plot of its distribution in ascending order, and it seems like tails are needed to be considered away from the body. | |
| Jan 25, 2016 at 20:15 | history | edited | Bear | CC BY-SA 3.0 |
added 148 characters in body
|
| Jan 25, 2016 at 19:14 | comment | added | Bear | I've plotted a scatter plot matrix. Hope it might be helpful | |
| Jan 25, 2016 at 19:13 | history | edited | Bear | CC BY-SA 3.0 |
added 129 characters in body
|
| Jan 25, 2016 at 18:59 | comment | added | Bear | Thank you. Nick. I'll look forward for quantile regression. How have you decided about quantile being more appropriate here? Only by evaluation metrics? | |
| Jan 25, 2016 at 18:55 | comment | added | Nick Cox | Your regressions are both fitted using least squares, That doesn't mean that a model better in those terms will ipso facto be better on MAE. If you want to use MAE, reach for quantile regression, which is closer to that. But the story looks bleak on this evidence: predictability for both is terrible and the low P-values are just side-effects of the sample size. You might be able to do better: a scatter plot matrix of A B C D might help us, but advising without sight of the data is difficult. | |
| Jan 25, 2016 at 18:50 | comment | added | Bear |
Yes, they both predict same variable. In fact, Model 2 = Model 1 without 2 regressors.
|
|
| Jan 25, 2016 at 18:48 | comment | added | gung - Reinstate Monica | "Both models predict some variable." Do the predict the same variable? Is it measured in the same units? | |
| Jan 25, 2016 at 18:45 | review | First posts | |||
| Jan 25, 2016 at 18:48 | |||||
| Jan 25, 2016 at 18:43 | history | asked | Bear | CC BY-SA 3.0 |