How can we specify a custom lambda sequence to glmnet

Question

I am new to the glmnet package in R, and wanted to specify a lambda function based on the suggestion in a published research paper to the glmnet.cv function. The documentation suggests that we can supply a decreasing sequence of lambdas as a parameter. However, in the documentation there are no examples of how to do this.

It would be very grateful if someone can suggest how to go about doing this. Do I pass a vector of 100 odd values (default value for nlambda) to the function? What restrictions should be there for the min and max value of this vector, if any? Also, are their things to keep in mind regarding nvars, nobs etc. while specifying the vector?

Thanks in advance.

Answer 1

This is fairly easy though it's not well explained in the original documentation ;)

In the following I've used cox family but you can change it based on your need

my_cvglmnet_fit <- cv.glmnet(x=regression_data, y=glmnet_response, family="cox", maxit = 100000)

Then you can plot the fitted object created by the cv.glmnet and in the plot you can easily see where the lambda is minimum. one of those dotted vertical lines is the minimum lambda and the other one is the 1se.

plot(my_cvglmnet_fit)

the following lines helps you see the non zero coefficients and their corresponding values:

coef(my_cvglmnet_fit, s = "lambda.min")[which(coef(my_cvglmnet_fit, s = "lambda.min") != 0)]  # the non zero coefficients
colnames(regression_data)[which(coef(my_cvglmnet_fit, s = "lambda.min") != 0)]  # The features that are selected

here are some links that may help:
http://web.stanford.edu/~hastie/glmnet/glmnet_alpha.html
http://blog.revolutionanalytics.com/2013/05/hastie-glmnet.html

Answer 2

You can define a grid like this :

    grid=10^seq(10,-2,length=100) ##get lambda sequence
    ridge_mod=glmnet(x,y,alpha=0,lambda=grid)