Geary on inference in multiple regression and on closeness and the Taxi problem
Citation:
John E. Spencer, Ann Largey, 'Geary on inference in multiple regression and on closeness and the Taxi problem', Economic & Social Studies, 1993Download Item:
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Abstract:
This paper deals with some minor aspects of Roy Geary's work. Two areas are selected
for discussion ? (a) his work with Leser on "paradoxical" situations in multiple regression and (b) his work on estimation of the unknown upper bound, N, of a uniform distribution, based on a sample of n values from that distribution. This work is explained, expanded and evaluated. The concept of "paradoxes" in multiple regression is slightly extended and applied to the case of estimating means in a multinomial situation with a known covariance matrix. Geary's estimator of N is compared with several other estimators, on the basis, inter alia, of mean squared errors, in both the cases of a continuous distribution and a discrete distribution sampling without replacement. In the latter case, a "large N minimum mean squared error" estimator is derived and assessed.
Author: Spencer, John E.; Largey, Ann
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Economic & Social StudiesType of material:
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Full text availableKeywords:
Statistical methods, Inference, Regression, Taxi problemISSN:
0012-9984Licences: