Suppose I have several predictors of interest. I also have a variable that I think will be important to control for.
What is the best way to handle this in an Adaptive LASSO?
One answer I've come across is to set lamda to 0 for the control variable. I'm curious whether to do this for the initial model as well as the re-scaling model?
But I've also now read about double selection methods for LASSO (though I haven't seen this for an adaptive LASSO), as well as talk of just partialling out the control variable. Others have said they just throw the control variable(s) in with the predictors of interest and let them all get shrunk together.
I'm curious to hear if there is a generally accepted best way to deal with control variables in an Adaptive LASSO.
What is the best way to handle this in an Adaptive LASSO?
One answer I've come across is to set lamda to 0 for the control variable. I'm curious whether to do this for the initial model as well as the re-scaling model?
But I've also now read about double selection methods for LASSO (though I haven't seen this for an adaptive LASSO), as well as talk of just partialling out the control variable. Others have said they just throw the control variable(s) in with the predictors of interest and let them all get shrunk together.
I'm curious to hear if there is a generally accepted best way to deal with control variables in an Adaptive LASSO.