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The Detection of Influential Observations for Allocation, Separation, and the Determination of Probabilities in a Bayesian Framework

Wesley Johnson
Journal of Business & Economic Statistics
Vol. 5, No. 3 (Jul., 1987), pp. 369-381
DOI: 10.2307/1391612
Stable URL: http://www.jstor.org/stable/1391612
Page Count: 13
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The Detection of Influential Observations for Allocation, Separation, and the Determination of Probabilities in a Bayesian Framework
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Abstract

Normal theory separation and allocation problems are discussed from a predictive point of view. Influence statistics are defined and employed to ascertain the impact that particular observations will have on the inferential goals--allocation of future observations, separation between populations, and the determination of probabilities for future cases. Methods are illustrated on a collection of financial data taken from Johnson and Wichern (1982).

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