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Use of minimum risk approach in the estimation of regression models with missing observations

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Abstract.

This article considers a linear regression model with some missing observations on the response variable and presents two estimators of regression coefficients employing the approach of minimum risk estimation. Small disturbance asymptotic properties of these estimators along with the traditional unbiased estimator are analyzed and conditions, that are easy to check in practice, for the superiority of one estimator over the other are derived.

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Authors and Affiliations

  1. Institut für Statistik, Universität München, Akademiestr. 1, 80799 München, Germany, , , , , , DE

    H. Toutenburg

  2. Department of Statistics, Panjab University, Chandigarh 160014, India, , , , , , IN

    Shalabh

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  1. H. Toutenburg
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  2. Shalabh
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Received May 2001

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Toutenburg, H., Shalabh, . Use of minimum risk approach in the estimation of regression models with missing observations. Metrika 54, 247–259 (2002). https://doi.org/10.1007/s184-002-8367-y

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  • DOI: https://doi.org/10.1007/s184-002-8367-y

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