Empirical assessment of the Maximum Likelihood Estimator quality in a parametric counting process model for recurrent events
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DOI: 10.1016/j.csda.2011.08.003
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References listed on IDEAS
- Jahn-Eimermacher, Antje, 2008. "Comparison of the Andersen-Gill model with poisson and negative binomial regression on recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4989-4997, July.
- Maja Miloslavsky & Sündüz Keleş & Mark J. van der Laan & Steve Butler, 2004. "Recurrent events analysis in the presence of time‐dependent covariates and dependent censoring," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 239-257, February.
- Jiang, S.T. & Landers, T.L. & Rhoads, T.R., 2005. "Semi-parametric proportional intensity models robustness for right-censored recurrent failure data," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 91-98.
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- Doyen, L., 2012. "Reliability analysis and joint assessment of Brown–Proschan preventive maintenance efficiency and intrinsic wear-out," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4433-4449.
- Doyen, L., 2014. "Semi-parametric estimation of Brown–Proschan preventive maintenance effects and intrinsic wear-out," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 206-222.
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Keywords
Counting process; Maximum likelihood; Recurrent events; Time-dependent covariate; Monte Carlo simulations; Random data generation; Asymptotic properties of the maximum likelihood estimator;All these keywords.
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