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Estimation of restricted regression model when disturbances are not necessarily normal

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  • Singh, R. Karan

Abstract

Considering a linear regression model subject to a set of linear restrictions binding the coefficients, two classes of estimators are proposed; their risk functions with respect to a general quadratic loss function are derived under non-normality, their properties are studied and the general dominance conditions of the two classes over the restricted regression estimator are also found.

Suggested Citation

  • Singh, R. Karan, 1994. "Estimation of restricted regression model when disturbances are not necessarily normal," Statistics & Probability Letters, Elsevier, vol. 19(2), pages 101-109, January.
    • Handle: RePEc:eee:stapro:v:19:y:1994:i:2:p:101-109
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    Cited by:

    1. Sanjay Verma & R. Karan Singh, 2002. "Estimation in restricted regression model with multivariate t distributed error," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 67-82.

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