Timeline for Why is Gaussian distribution used for Maximum Likelihood estimation with Linear Regression and not some other distribution? [duplicate]
Current License: CC BY-SA 4.0
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| when toggle format | what | by | license | comment | |
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| Sep 25, 2018 at 13:55 | comment | added | Glen_b | There's also nothing stopping you optimizing another loss function even if it isn't ML for some distribution. | |
| Sep 25, 2018 at 13:47 | history | closed |
mkt Ferdi Glen_b normal-distribution Users with the normal-distribution badge or a synonym can single-handedly close normal-distribution questions as duplicates and reopen them as needed. |
Duplicate of How does linear regression use the normal distribution? | |
| Sep 25, 2018 at 13:42 | comment | added | Glen_b | There's nothing stopping you choosing another distribution. Regression models using other conditional distributions are certainly used in practice. For example: 1. Regression with Laplace errors, for which MLE is L1 regression 2. Generalized linear models, which are ML for distributions in the exponential family. If you choose an identity link you have a model where the conditional mean is linear in the predictors 3. M-estimators for which the $\rho$ function is the negative log of an actual density 4. regression using t-errors, which crop up in a number of applications | |
| Sep 25, 2018 at 13:25 | review | Close votes | |||
| Sep 25, 2018 at 13:50 | |||||
| Sep 25, 2018 at 12:40 | review | First posts | |||
| Sep 25, 2018 at 12:58 | |||||
| Sep 25, 2018 at 12:39 | history | asked | Nagabhushan Baddi | CC BY-SA 4.0 |