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Bayes prediction of the regression coefficient in a finite population using balanced loss function

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  • Ashok K. Bansal
  • Priyanka Aggarwal

Abstract

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Suggested Citation

  • Ashok K. Bansal & Priyanka Aggarwal, 2009. "Bayes prediction of the regression coefficient in a finite population using balanced loss function," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 1-16.
  • Handle: RePEc:mtn:ancoec:090101
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    File URL: ftp://metron.sta.uniroma1.it/RePEc/articoli/2009-1-1.pdf
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    References listed on IDEAS

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    1. Haitao Chu & Lawrence H. Moulton & Wendy J. Mack & Douglas J. Passaro & Paulo F. Barroso & Alvaro Muñoz, 2005. "Correlating two continuous variables subject to detection limits in the context of mixture distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 831-845.
    2. Srabashi Basu & Ayanendranath Basu & M. Jones, 2006. "Robust and Efficient Parametric Estimation for Censored Survival Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(2), pages 341-355, June.
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    Cited by:

    1. Hu, Guikai & Li, Qingguo & Yu, Shenghua, 2014. "Optimal and minimax prediction in multivariate normal populations under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 154-164.
    2. Peng, Ping & Hu, Guikai & Liang, Jian, 2015. "All admissible linear predictors in the finite populations with respect to inequality constraints under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 113-122.

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