# Eilers & Marx parameterization

Parameterization of the spline from Eilers & Marx (1996)

**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)