Timeline for How to bound the output of a regression model?
Current License: CC BY-SA 3.0
6 events
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| Mar 14, 2012 at 10:49 | comment | added | Peter Ellis | But in any event, +1 for Wayne's answer because I think the fundamental issue is that: rather than trying to constrain the results of an OLS regression, you should try to use some other kind of model, probably still a generalized linear model but not with a gaussian response. | |
| Mar 13, 2012 at 23:49 | comment | added | Wayne | @Denise: Have you tried Poisson regression on the two events and divide? Might work a lot better than the division you did previously between the two improper regressions. | |
| Mar 13, 2012 at 13:49 | comment | added | Denise | that might work, except that the number of impressions is unknown as well. | |
| Mar 12, 2012 at 22:03 | comment | added | boscovich | Then you could model the number of clicks using a Poisson or Negative Binomial regression as suggested by @Wayne and treat the impressions (number of times the ad is shown) as the offset. | |
| Mar 12, 2012 at 21:37 | comment | added | Denise | it's sort-of count data. I'm modeling a ratio of two events (think, something like click-through-rate). I thought about predicting the number of the two separate events and then dividing, but it actually didn't turn out as well as just predicting the ratio. | |
| Mar 12, 2012 at 21:25 | history | answered | Wayne | CC BY-SA 3.0 |