如何在R中的cv.glmnet或glmnet函数中找到拟合值？

Question

Suppose I have generated the following data set and fitted the model using cv.glmnet function in R .

library(glmnet)
means <- c(-1, 1.3, 0.6, 2, 1.5, -0.7, 2.5)
size <- c(50, 50, 100, 200, 350, 50, 200)


t = list()
  for (i in 1:length(means)) {
   t[[i]] <- c(rnorm(size[i],mean = means[i],sd = 0.5))
  }
y <- c(unlist(t))
plot(y,type = 'l')

lower_tri <- function(i){ 
  a <- matrix(1,i,i)
  a[upper.tri(a)] <- 0
  return(a)
}
x <- lower_tri(sum(size))[,2:sum(size)]

cv_fit <- cv.glmnet(x,y)

How to find the fitted value using cv_fit1 ? I used fitted() function for lm model.

Thank you very much.

Answer 1

Asking for the fitted values of a cv.glmnet -object from pkg glmnet is wrong headed. Cross-validation is being done on a relatively wide variety of models with varying structures, so it's not really doing anything equivalent to glm which has a single model and a single result. The goal of cv.glmnet it to give you results that let you choose the optimal level of complexity of the glmnet procedure given the nature of your data. It is a step on the way to choosing a glmnet model, ie choosing lambda. You could use this to get a prediction:

 predict( glmnet(x,y), s=cv_fit$lambda.min )  

I don't see the example offered as being particularly useful to support further discussion since it appears rather "degenerate" with a minimal level of complexity.