Linked Questions

2
votes
1answer
180 views

Intuition on simple linear regression signal plus noise model

I'm currently studying linear regression on this book "F.M. Dekking - A Modern Introduction to Probability and Statistics: Understanding Why and How" where the signal+noise model is presented: $Y_i =...
0
votes
1answer
102 views

Is possible to perform a linear regression using log-normal priors?

I am trying to do a Bayesian linear regression. Since my data cannot be negative a gave them a log-Normal distribution, but I am not sure if the priors should be positive also. If I write my model ...
1
vote
1answer
64 views

Extra information at prediction time when using a Bayesian logistic regression vs. normal

I have a binary classification problem (i.e. is observation positive or negative) and I'm interested in what information I can obtain about observations in my test set. I don't care about the model ...
0
votes
1answer
44 views

what is the posterior in the case of regression

I am having trouble "mapping" the variables in the Bayes equation onto the case of regression. As notation, say $$ P(\theta|D) = \frac{P(D|\theta) P(\theta)}{ P(D) } $$ I have come to think of $\...
0
votes
1answer
18 views

Placing constraints on linear model coefficients

I have this bit of data : ...
0
votes
1answer
18 views

Using prior knowledge about correlated variable in ridge regression

I am wondering what methods are available for incorporating prior knowledge of some variable that is correlated with the unknown regression coefficients in a ridge regression. I have a sparse matrix ...

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