IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2007i12p6614-6623.html
   My bibliography  Save this article

Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm

Author

Listed:
  • Wang, Xiaoning
  • Schumitzky, Alan
  • D'Argenio, David Z.

Abstract

No abstract is available for this item.

Suggested Citation

  • Wang, Xiaoning & Schumitzky, Alan & D'Argenio, David Z., 2007. "Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6614-6623, August.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:12:p:6614-6623
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(07)00114-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. A. Philippou & G. Roussas, 1975. "Asymptotic normality of the maximum likelihood estimate in the independent not identically distributed case," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 27(1), pages 45-55, December.
    3. Kuhn, E. & Lavielle, M., 2005. "Maximum likelihood estimation in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1020-1038, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Xiaoning & Schumitzky, Alan & D'Argenio, David Z., 2009. "Population pharmacokinetic/pharmacodynamic mixture models via maximum a posteriori estimation," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3907-3915, October.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    2. Fernandez-Cornejo, Jorge & Wechsler, Seth James, 2012. "Fifteen Years Later: Examining the Adoption of Bt Corn Varieties by U.S. Farmers," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124257, Agricultural and Applied Economics Association.
    3. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    4. Hajargasht, Gholamreza & Rao, D.S. Prasada, 2019. "Multilateral index number systems for international price comparisons: Properties, existence and uniqueness," Journal of Mathematical Economics, Elsevier, vol. 83(C), pages 36-47.
    5. Cranfield, John A.L. & Preckel, Paul V. & Liu, Songquan, 1997. "Approximating Bayesian Posteriors using Multivariate Gaussian Quadrature," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35791, Western Agricultural Economics Association.
    6. Troske, Kenneth R. & Voicu, Alexandru, 2010. "Joint estimation of sequential labor force participation and fertility decisions using Markov chain Monte Carlo techniques," Labour Economics, Elsevier, vol. 17(1), pages 150-169, January.
    7. Ardia, David & Hoogerheide, Lennart F., 2010. "Efficient Bayesian estimation and combination of GARCH-type models," MPRA Paper 22919, University Library of Munich, Germany.
    8. Mengheng Li & Ivan Mendieta‐Muñoz, 2020. "Are long‐run output growth rates falling?," Metroeconomica, Wiley Blackwell, vol. 71(1), pages 204-234, February.
    9. Arimura, Toshi H. & Darnall, Nicole & Katayama, Hajime, 2011. "Is ISO 14001 a gateway to more advanced voluntary action? The case of green supply chain management," Journal of Environmental Economics and Management, Elsevier, vol. 61(2), pages 170-182, March.
    10. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
    11. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    12. Goldman Elena & Tsurumi Hiroki, 2005. "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-38, June.
    13. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
    14. İsmail Başoğlu & Wolfgang Hörmann & Halis Sak, 2018. "Efficient simulations for a Bernoulli mixture model of portfolio credit risk," Annals of Operations Research, Springer, vol. 260(1), pages 113-128, January.
    15. Borowska, Agnieszka & Hoogerheide, Lennart & Koopman, Siem Jan & van Dijk, Herman K., 2020. "Partially censored posterior for robust and efficient risk evaluation," Journal of Econometrics, Elsevier, vol. 217(2), pages 335-355.
    16. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    17. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    18. Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Inference under Sampling from Scale Mixtures of Normals," Discussion Paper 1996-02, Tilburg University, Center for Economic Research.
    19. Boneva, T. & Golin, M. & Kaufmann, K. & Rauh, C., 2022. "Beliefs About Maternal Labor Supply," Janeway Institute Working Papers 2230, Faculty of Economics, University of Cambridge.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:51:y:2007:i:12:p:6614-6623. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.