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A Bivariate Weibull Regression Model

Author

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  • Hanagal David D.

    (Department of Statistics, University of Pune, Pune-411007, India)

Abstract

In this paper, we propose a new bivariate Weibull regression model based on censored samples with common covariates. There are some interesting biometrical situations which motivate the study of a bivariate Weibull regression model of the proposed type. A procedure for obtaining the maximum likelihood estimators for the parameters in the model is derived and a test of significance for the regression parameters is sketched.

Suggested Citation

  • Hanagal David D., 2005. "A Bivariate Weibull Regression Model," Stochastics and Quality Control, De Gruyter, vol. 20(1), pages 143-150, January.
    • Handle: RePEc:bpj:ecqcon:v:20:y:2005:i:1:p:143-150:n:3
    DOI: 10.1515/EQC.2005.143
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    Citations

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    Cited by:

    1. Kundu, Debasis & Dey, Arabin Kumar, 2009. "Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 956-965, February.
    2. Nandi, Swagata & Dewan, Isha, 2010. "An EM algorithm for estimating the parameters of bivariate Weibull distribution under random censoring," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1559-1569, June.
    3. David Hanagal, 2009. "Weibull extension of bivariate exponential regression model with different frailty distributions," Statistical Papers, Springer, vol. 50(1), pages 29-49, January.

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