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Parametric Bivariate Regression Analysis Based on Censored Samples: A Weibull 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 bivariateWeibull distribution and derive estimation and test procedures based on censored samples with common covariates. The study of bivariate Weibull was motivated by interesting biometrical applications. The maximum likelihood estimators for the model parameters are obtained together with a test of significance.

Suggested Citation

  • Hanagal David D., 2004. "Parametric Bivariate Regression Analysis Based on Censored Samples: A Weibull Model," Stochastics and Quality Control, De Gruyter, vol. 19(1), pages 83-90, January.
    • Handle: RePEc:bpj:ecqcon:v:19:y:2004:i:1:p:83-90:n:10
    DOI: 10.1515/EQC.2004.83
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    Citations

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    Cited by:

    1. David Hanagal, 2009. "Weibull extension of bivariate exponential regression model with different frailty distributions," Statistical Papers, Springer, vol. 50(1), pages 29-49, January.
    2. Hanagal, David D., 2008. "Modelling heterogeneity for bivariate survival data by the log-normal distribution," Statistics & Probability Letters, Elsevier, vol. 78(9), pages 1101-1109, July.
    3. David Hanagal, 2010. "Modeling heterogeneity for bivariate survival data by the Weibull distribution," Statistical Papers, Springer, vol. 51(4), pages 947-958, December.
    4. Hanagal, David D., 2010. "Modeling heterogeneity for bivariate survival data by the compound Poisson distribution with random scale," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1781-1790, December.

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