Statistical Modelling 2 (2002), 333–349
Flexible smoothing with P-splines: a unified approach
I D Currie
Department of Actuarial Mathematics and Statistics,
Heriot-Watt University,
Edinburgh, EH14 4AS,
UK.
eMail:
I.D.Currie@ma.hw.ac.uk
M Durban
Departamento de Estadistica y Econometria,
Universidad Carlos III de Madrid,
Edificio Torres Quevedo,
28911 Leganes,
Madrid,
Spain.
eMail:
mdurban@est-econ.uc3m.es
Abstract:
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.
Keywords:
Heterogeneity; mixed models; P-splines; REML; semiparametric models; serial
correlation.
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