Timeline for The mean and variance of Poisson distribution are equal
Current License: CC BY-SA 4.0
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| Jan 18, 2023 at 3:05 | history | edited | User1865345 | CC BY-SA 4.0 |
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| Sep 30, 2017 at 12:59 | comment | added | whuber♦ | Search for "deviance residuals." | |
| Sep 30, 2017 at 4:05 | history | edited | sree22 | CC BY-SA 3.0 |
Pros and cons of poisson GLM
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| Sep 30, 2017 at 3:46 | history | edited | sree22 | CC BY-SA 3.0 |
added 38 characters in body
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| Sep 30, 2017 at 3:42 | comment | added | sree22 | @whuber I seem to have explained reasons for using Poisson, instead of problems associated with it. Can you please explain how residuals in a GLM are interpreted ? | |
| Sep 29, 2017 at 19:38 | comment | added | whuber♦ |
This answer seems to miss the mark. The Poisson distribution usually concerns count data. Ordinary least squares, as implemented by lm, is typically inappropriate: a generalized linear model, such as implemented by glm, is more suitable. The residuals will differ from what you show here, and so does their analysis. Furthermore, Poisson regression is perfectly capable of handling heteroscedasticity--any nonzero trend will (almost by definition) be heteroscedastic. The issue is that it might not be a sufficiently flexible method for modeling the heteroscedasticity in some cases.
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| Sep 29, 2017 at 18:20 | history | answered | sree22 | CC BY-SA 3.0 |