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The Effects of Model Misspecification, Conditions for Robustness, and Bayesian Modeling

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Prediction Theory for Finite Populations

Part of the book series: Springer Series in Statistics ((SSS))

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Abstract

As seen in the previous chapters, the optimality of predictors of population quantities might strongly depend on the particular model under which they have been derived. For example, if one assumes model SM2 (model ψ), as the working model, the ψ-BLUP of the population total is the ratio predictor

$${\hat T_R} = n{\bar y_s} + \frac{{{{\bar y}_s}}}{{{{\bar x}_s}}}\left( {N - n} \right){\bar x_r}$$

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© 1992 Springer-Verlag New York Inc.

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Bolfarine, H., Zacks, S. (1992). The Effects of Model Misspecification, Conditions for Robustness, and Bayesian Modeling. In: Prediction Theory for Finite Populations. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2904-9_7

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  • DOI: https://doi.org/10.1007/978-1-4612-2904-9_7

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7713-2

  • Online ISBN: 978-1-4612-2904-9

  • eBook Packages: Springer Book Archive

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