[R] Package for penalized multivariate Regression

Dominik Schmidt @chm|dtdom|n|k22 @end|ng |rom gm@||@com
Sun Apr 28 13:52:00 CEST 2019

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,


	[[alternative HTML version deleted]]

More information about the R-help mailing list