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Time-dependent coefficients in a Cox-type regression model


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  • Murphy, S. A.
  • Sen, P. K.
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    Estimation of a time-varying coefficient in a Cox-type parameterization of the stochastic intensity of a point process is considered. A sieve estimation procedure (Grenander, 1981) is used to estimate the coefficient. A rate of convergence in probability for the sieve estimator is given and a functional CLT for the integrated sieve estimator is proved.

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    Bibliographic Info

    Article provided by Elsevier in its journal Stochastic Processes and their Applications.

    Volume (Year): 39 (1991)
    Issue (Month): 1 (October)
    Pages: 153-180

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    Handle: RePEc:eee:spapps:v:39:y:1991:i:1:p:153-180

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    Related research

    Keywords: counting processes Cox regression martingales method of sieves;


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    Cited by:
    1. Bhattacharjee, Arnab, 2004. "A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models," MPRA Paper 3937, University Library of Munich, Germany.
    2. Bianca Teodorescu & Ingrid Keilegom & Ricardo Cao, 2010. "Generalized time-dependent conditional linear models under left truncation and right censoring," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(3), pages 465-485, June.
    3. Loki Natarajan & John O'Quigley, 2002. "Predictive capability of stratified proportional hazards models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(8), pages 1153-1163.
    4. Bhattacharjee, A., 2003. "Estimation in Hazard Regression Models under Ordered Departures from Proportionality," Cambridge Working Papers in Economics 0337, Faculty of Economics, University of Cambridge.
    5. Osman, Muhtarjan & Ghosh, Sujit K., 2012. "Nonparametric regression models for right-censored data using Bernstein polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 559-573.
    6. Arnab Bhattacharjee, 2005. "Models of Firm Dynamics and the Hazard Rate of Exits: Reconciling Theory and Evidence using Hazard Regression Models," Econometrics 0503021, EconWPA.
    7. Chin-Tsang Chiang, 2011. "A more flexible joint latent model for longitudinal and survival time data," Metrika, Springer, vol. 73(2), pages 151-170, March.
    8. Li, Jianbo & Zhang, Riquan, 2011. "Partially varying coefficient single index proportional hazards regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 389-400, January.
    9. Bhattacharjee, A. & Samarjit Das, 2002. "Testing Proportionality in Duration Models with Respect to Continuous Covariates," Cambridge Working Papers in Economics 0220, Faculty of Economics, University of Cambridge.
    10. Bhattacharjee, A., 2004. "A Simple Test for the Absence of Covariate Dependence in Duration Models," Cambridge Working Papers in Economics 0401, Faculty of Economics, University of Cambridge.
    11. Arnab Bhattacharjee, 2009. "Testing for Proportional Hazards with Unrestricted Univariate Unobserved Heterogeneity," Discussion Paper Series, Department of Economics 200904, Department of Economics, University of St. Andrews.
    12. Arnab Bhattacharjee & Chris Higson & Sean Holly & Paul Kattuman, 2007. "Macroeconomic Conditions and Business Exit: Determinants of Failures and Acquisitions of UK Firms," CDMA Working Paper Series 200713, Centre for Dynamic Macroeconomic Analysis.
    13. Chin-Tsang Chiang & Mei-Cheng Wang, 2009. "Varying-coefficient model for the occurrence rate function of recurrent events," Annals of the Institute of Statistical Mathematics, Springer, vol. 61(1), pages 197-213, March.


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