I have done a ridge regression using the 'glmnet' function in R. Then, after finding the optimal lambda parameter, I checked what are the predictors' beta coefficients by extracting glmnet.fit$beta when the lambda is the optimal lambda. All the predictors were scales (mean=0, sd=1) prior to the analysis).
My question is: what do the numbers say?
I assume that the coefficients are not standardized betas. So, are they similar to non-standardized regression coefficients in other regressions? Do they have a certain scale? and if so, what is this scale based on? For example, what is the meaning of a coefficient with a value of.05?
Would appreciate your help and clarification very much.