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Rank Estimators Versus Least Square Estimators for Estimating the Parameters of Semiparametric Accelerated Failure Time Model

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  • Mostafa Karimi
  • Noor Akma Ibrahim

    (Department of Mathematics, University Putra Malaysia, Malaysia)

Abstract

Rank-based method and least square approach are the most common techniques for estimating the regression parameters of accelerated failure time model. In this paper, both inference procedures are considered, their advantages and disadvantages are explained, and their similarities and differences are discussed.

Suggested Citation

  • Mostafa Karimi & Noor Akma Ibrahim, 2019. "Rank Estimators Versus Least Square Estimators for Estimating the Parameters of Semiparametric Accelerated Failure Time Model," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(2), pages 34-36, February.
    • Handle: RePEc:adp:jbboaj:v:9:y:2019:i:2:p:34-36
    DOI: 10.19080/BBOAJ.2019.09.555757
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    References listed on IDEAS

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    1. Zhezhen Jin & D. Y. Lin & Zhiliang Ying, 2006. "On least-squares regression with censored data," Biometrika, Biometrika Trust, vol. 93(1), pages 147-161, March.
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