Statistical Modelling 4 (2004), 314–323
Classification of longitudinal profiles based on semi-parametric
regression with mixed effects
Christian Pfeifer
Institut für Statistik,
Universität Innsbruck,
Universitätsstraße 15,
A-6020 Innsbruck,
Austria
eMail:
christian.pfeifer@uibk.ac.at
Abstract:
A semi-parametric model is applied in order to model counts of
letters for the federal Austrian postal system. Random coefficients
are introduced into the splined variable of the semi-parametric
regression model to describe heterogeneity of the temporal effect.
Pfeifer and Seeber propose estimates for random coefficients to
classify post offices by a hierarchical cluster algorithm. In this
article, we apply two model based approaches for classification.
It turns out here that both the hierarchical and the model based
approach are useful for explorative cluster analysis.
Keywords:
cluster analysis; heterogeneity model; linear mixed effects model;
nonparametric maximum likelihood; semi-parametric regression
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