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XV.—On the Estimation of Statistical Parameters

Published online by Cambridge University Press:  14 February 2012

A. C. Aitken  and
H. Silverstone
A. C. Aitken
Affiliation:
Mathematical Institute, University of Edinburgh
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Summary

In the problem of estimating from sample the value of a parameter in a probability function new postulates are suggested of unbiased linear estimate and minimum sampling variance. A comparison is made, with illustrative examples, between this method and the principle of maximum likelihood, and ground common to the two is traversed. The new postulates are also placed in relation to the theory of sufficient statistics.

Type
Research Article
Information
Proceedings of the Royal Society of Edinburgh Section A: Mathematics , Volume 61 , Issue 2 , 1942 , pp. 186 - 194
Copyright
Copyright © Royal Society of Edinburgh 1942

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References

References to Literature

Fisher, R. A., 1921. “On the mathematical foundations of theoretical statistics,” Phil. Trans., A, vol. ccxxii, pp. 309–368.Google Scholar
Koopman, B. O., 1936. “On distributions admitting a sufficient statistic,” Trans. Amer. Math. Soc, vol. xxxix, pp. 399–409.CrossRefGoogle Scholar