Dear all, I want to do a multivariate regression. So I have Y which is a matrix and one vector x which is my predictor variable. I want to do a multivariate regression with penalizing the coefficients I get. Something like: $||y-xb|| + \lambda b^t P b $ But I have a "own" penalty term which I want to use for penalized regression.
When I searched for penalized regression, I found a lot of packages but all of them have predefined penalties like lasso, ridge or second differences. I used the gam() package in mgcv when I had an univariate response: gam(Y~x_1, paraPen = penaltymatrix) but this package do not support multivariate regression. Is there any R package where I can use an individual penalty matrix to my coefficients? Or can you give me any advice how I solve the problem I have? Kind regards, Dominik [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.