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Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data

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  • Gang Cheng
  • Ying Zhang
  • Liqiang Lu

Abstract

Nonparametric and semi-parametric analysis of panel count data have recently been active research topics in statistical literature. The maximum likelihood method based on the non-homogeneous Poisson process has been proved an efficient inference procedure for such analysis. However, computing the non- and semi-parametric maximum likelihood estimates (MLEs) can be very intensive numerically and the available methods are not efficient. In this manuscript, we develop an efficient numerical algorithm stemming from the Newton–Raphson method to compute the non- and semi-parametric MLEs for panel count data. Simulation studies are carried out to demonstrate the numerical efficiency of the proposed algorithm compared to the existing methods in the literature.

Suggested Citation

  • Gang Cheng & Ying Zhang & Liqiang Lu, 2011. "Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 567-579.
  • Handle: RePEc:taf:gnstxx:v:23:y:2011:i:2:p:567-579
    DOI: 10.1080/10485252.2010.548521
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    References listed on IDEAS

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    1. Jianguo Sun, 2003. "A nonparametric test for panel count data," Biometrika, Biometrika Trust, vol. 90(1), pages 199-208, March.
    2. Ying Zhang & Mortaza Jamshidian, 2003. "The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data," Biometrics, The International Biometric Society, vol. 59(4), pages 1099-1106, December.
    3. Lu, Minggen & Zhang, Ying & Huang, Jian, 2009. "Semiparametric Estimation Methods for Panel Count Data Using Monotone B-Splines," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1060-1070.
    4. X. Joan Hu & Jianguo Sun & Lee‐Jen Wei, 2003. "Regression Parameter Estimation from Panel Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 25-43, March.
    5. J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate‐dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
    6. X. Joan Hu & Stephen W. Lagakos & Richard A. Lockhart, 2009. "Marginal analysis of panel counts through estimating functions," Biometrika, Biometrika Trust, vol. 96(2), pages 445-456.
    7. Ying Zhang, 2002. "A semiparametric pseudolikelihood estimation method for panel count data," Biometrika, Biometrika Trust, vol. 89(1), pages 39-48, March.
    8. Ying Zhang, 2006. "Nonparametric k-sample tests with panel count data," Biometrika, Biometrika Trust, vol. 93(4), pages 777-790, December.
    9. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    10. Chiung-Yu Huang & Mei-Cheng Wang & Ying Zhang, 2006. "Analysing panel count data with informative observation times," Biometrika, Biometrika Trust, vol. 93(4), pages 763-775, December.
    11. Zhuoxin Sun & Ori Rosen & Allan R. Sampson, 2007. "Multivariate Bernoulli Mixture Models with Application to Postmortem Tissue Studies in Schizophrenia," Biometrics, The International Biometric Society, vol. 63(3), pages 901-909, September.
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    1. Liang Zhu & Ying Zhang & Yimei Li & Jianguo Sun & Leslie L. Robison, 2018. "A semiparametric likelihood†based method for regression analysis of mixed panel†count data," Biometrics, The International Biometric Society, vol. 74(2), pages 488-497, June.
    2. Yimei Li & Liang Zhu & Lei Liu & Leslie L. Robison, 2021. "Regression Analysis of Mixed Panel-Count Data with Application to Cancer Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(1), pages 178-195, April.
    3. Audrey Boruvka & Richard J. Cook, 2015. "A Cox-Aalen Model for Interval-censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 414-426, June.

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