A semiparametric mixture regression model for longitudinal data
Nummi, Tapio; Salonen, Janne; Koskinen, Lasse; Pan, Jianxin (2017-04-05)
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Nummi, Tapio
Salonen, Janne
Koskinen, Lasse
Pan, Jianxin
Grace Scientific Pub.
05.04.2017
Journal of Statistical Theory and Practice : 1
Tiivistelmä
A normal semiparametric mixture regression model is proposed for longitudinal data. The proposed model contains one smooth term and a set of possible linear predictors. Model terms are estimated using the penalized likelihood method with the EM algorithm. A computationally feasible alternative method that provides an approximate solution is also introduced. Simulation experiments and a real data example are used to illustrate the methods.
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