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Technical Note—Variate Generation for Accelerated Life and Proportional Hazards Models

Author

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  • Lawrence M. Leemis

    (University of Oklahoma, Norman, Oklahoma)

Abstract

We use accelerated life and proportional hazards lifetime models to account for the effects of covariates on a random lifetime. We find that variate generation algorithms for Monte Carlo simulation in both the renewal and nonhomogeneous Poisson process cases are a simple extension of the inverse cumulative distribution function (cdf) technique.

Suggested Citation

  • Lawrence M. Leemis, 1987. "Technical Note—Variate Generation for Accelerated Life and Proportional Hazards Models," Operations Research, INFORMS, vol. 35(6), pages 892-894, December.
    • Handle: RePEc:inm:oropre:v:35:y:1987:i:6:p:892-894
    DOI: 10.1287/opre.35.6.892
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    Cited by:

    1. R. Guo & C. E. Love, 1994. "Simulating nonhomogeneous poisson processes with proportional intensities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(4), pages 507-522, June.
    2. Yunda Huang & Yuanyuan Zhang & Zong Zhang & Peter B. Gilbert, 2020. "Generating Survival Times Using Cox Proportional Hazards Models with Cyclic and Piecewise Time-Varying Covariates," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 324-339, December.
    3. Adam Braima S. Mastor & Abdulaziz S. Alghamdi & Oscar Ngesa & Joseph Mung’atu & Christophe Chesneau & Ahmed Z. Afify, 2023. "The Extended Exponential-Weibull Accelerated Failure Time Model with Application to Sudan COVID-19 Data," Mathematics, MDPI, vol. 11(2), pages 1-26, January.

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