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Flexible smoothing with P-splines: a unified approach

Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, UK, I.D.Currie{at}ma.hw.ac.uk

M Durban

Departamento de Estadistica y Econometria, Universidad Carlos III de Madrid, Madrid, Spain

We consider the application of P-splines (Eilers and Marx, 1996) to three classes of models with smooth components: semiparametric models, models with serially correlated errors, and models with heteroscedastic errors. We show that P-splines provide a common approach to these problems. We set out a simple nonparametric strategy for the choice of the P-spline parameters (the number of knots, the degree of the P-spline, and the order of the penalty) and use mixed model (REML) methods for smoothing parameter selection. We give an example of a model in each of the three classes and analyse appropriate data sets.

Key Words: heterogeneity • mixed models • P-splines • REML • semiparametric models • serial correlation

Statistical Modelling, Vol. 2, No. 4, 333-349 (2002)
DOI: 10.1191/1471082x02st039ob


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