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- Priors are a key component of Bayesian modelling.
| prior | posterior |
| Prior is a belief you have on some quantity, typically on a set of parameters, without having any look at the data |
If data is involved, the belief you have is updated and is called as posterior. |
The Gaussian prior on the coefficients
→ coefficients are assumed to be distributed according to Gaussian/Normal distribution.
!= Gaussian prior over the error terms
→ Those are two different assumptions with very different effects
https://stats.stackexchange.com/questions/476706/what-does-it-mean-to-have-a-gaussian-prior
What does it mean to have a "gaussian prior?"
When reading up on ridge regression, I saw it stated that it has a "gaussian prior." I realized that I don't know what the word prior means in this context and what it is applied to? I sh...
stats.stackexchange.com
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