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A linearization procedure and a VDM/ECM algorithm for penalized and constrained nonparametric maximum likelihood estimation for mixture models

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  • Wang, Ji-Ping

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  • Wang, Ji-Ping, 2007. "A linearization procedure and a VDM/ECM algorithm for penalized and constrained nonparametric maximum likelihood estimation for mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2946-2957, March.
  • Handle: RePEc:eee:csdana:v:51:y:2007:i:6:p:2946-2957
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    1. R. DerSimonian, 1986. "Maximum Likelihood Estimation of a Mixing Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(3), pages 302-309, November.
    2. Wang, Ji-Ping Z. & Lindsay, Bruce G., 2005. "A Penalized Nonparametric Maximum Likelihood Approach to Species Richness Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 942-959, September.
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    Cited by:

    1. Laurent Cavalier & Nicolas Hengartner, 2009. "Estimating linear functionals in Poisson mixture models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(6), pages 713-728.
    2. Yangxin Huang & Xiaosun Lu & Jiaqing Chen & Juan Liang & Miriam Zangmeister, 2018. "Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(4), pages 699-718, October.
    3. Antic, J. & Laffont, C.M. & Chafaï, D. & Concordet, D., 2009. "Comparison of nonparametric methods in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 642-656, January.
    4. Fu, Liyong & Wang, Mingliang & Lei, Yuancai & Tang, Shouzheng, 2014. "Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 173-183.

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