I have a question regarding the interpretation of the trace of coefficients when running Elastic net with the package glmnet in R.
This is the plot I obtain with alpha = 0.5
My understanding is that the numbers on the top are the number of non-zero coefficients included in the model at the given value of lambda (and alpha).
I have trouble understanding why the number of non-zero coefficients suddenly starts increasing with lambda? I would expect more variable coefficients be set to zero as lambda increases, from looking at the formula for the elastic net penalty.
I am hoping someone can explain if the pattern I see is due to an error that I made, me misinterpreting the graph, or something that can be rationally explained.
I used the following code:
fit.elnet <- glmnet(x.train, y.train, family="gaussian", alpha=.5)
Where y.train contains only the time series of prices i am trying to explain and x.train contains only timeseries of explanatory variables. The data has high multicollinearity, if that is in any way useful.