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Journal of Statistical Theory and Practice

, Volume 12, Issue 1, pp 12–22 | Cite as

A semiparametric mixture regression model for longitudinal data

  • Tapio Nummi
  • Janne Salonen
  • Lasse Koskinen
  • Jianxin Pan
Article

Abstract

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.

Keywords

Curve clustering EM algorithm finite mixtures growth curves 

AMS Subject Classification

62G05 62B99 62J07 

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Copyright information

© Grace Scientific Publishing, 20 Middlefield Ct, Greensboro, NC 27455 2018

Authors and Affiliations

  • Tapio Nummi
    • 1
  • Janne Salonen
    • 2
  • Lasse Koskinen
    • 3
  • Jianxin Pan
    • 4
  1. 1.Faculty of Natural SciencesUniversity of TampereTampereFinland
  2. 2.Research DepartmentThe Finnish Centre for PensionsHelsinkiFinland
  3. 3.Faculty of ManagementUniversity of TampereTampereFinland
  4. 4.School of MathematicsThe University of ManchesterManchesterUnited Kingdom

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