A constrained spline estimator of a hazard function

A constrained quadratic spline is proposed as an estimator of the hazard function of a random variable. A maximum penalized likelihood procedure is used to fit the estimator to a sample of psychological response times. The results of a small simulation study suggest that, with a sample size of 500, the procedure may provide a reasonably precise estimate of the shape of a hazard function.This research was conducted under the auspices of the Naval Postgraduate School during the author's sabbatical from Vanderbilt University and was partially supported by the Navy Personnal Research and Development Center. The author wishes to thank Jules Borack, Richard Sorenson, and two anonymous reviewers for a number of useful and stimulating comments on the work reported here. Thanks are also due to David Kohfeld for providing the data which were used in the empirical example.