Simulate a binary logistic model for n = 300 with an average fraction of events somewhere between 0.15 and 0.3. Use 5 continuous covariates and assume the model is everywhere linear. Fit an unpenalized model, then solve for the optimum quadratic penalty λ. Relate the resulting effective d.f. to the 15:1 rule of thumb, and compute the heuristic shrinkage coefficient ˆγ for the unpenalized model and for the optimally penalized model, inserting the effective d.f. for the number of non-intercept parameters in the model.