GAMs implemented as random effects

Model description

Since their introduction by Hastie & Tibshirani in the late 80ies, GAM's have become very popular. This example shows how to fit a GAM using penalized splines. The reason why GAM's can easily be handled in ADMB-RE is that penalized splines are a special case of random effects. ADMB-RE automatically estimates the degrees of freedom for each spline component, as this only amounts to estimate the variance of the random effects. A more detailed discussion of the model and the estimation approach can be found here: union.pdf

 

The data, which are available from Statlib (lib.stat.cmu.edu/), contain information for each of 534 workers about whether they are members (y=1) of a workers union or not (y=0). The goal is to model the probability of membership as a function of various covariates.

 

Details

union.pdf

 

Files

See "Navigation" box to the left.

• .tpl:  Model file
• .dat: Data file
• .pin: Starting values for the numerical optimizer
  
• .par: Result file (what you get when you compile and run your model)