The Construction of Good Linear Unbiased Estimates from the Best Linear Estimates for a Smaller Sample Size

John I. McCool

doi:10.1080/00401706.1965.10490297

The Construction of Good Linear Unbiased Estimates from the Best Linear Estimates for a Smaller Sample Size

John I. McCool

Engineering Division (Great Valley)

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

A general procedure is found for constructing good unbiased linear estimators of the location and scale parameters of a distribution for use with an uncensored sample of size n. It is presupposed that the coefficients of the best linear estimates are available for an uncensored sample of size m < n for the distribution under investigation. The coefficients of the proposed estimators are obtained as linear combinations of these with the aid of tabled values of the hypergeometric probability function.

Original language	English (US)
Pages (from-to)	543-552
Number of pages	10
Journal	Technometrics
Volume	7
Issue number	4
DOIs	https://doi.org/10.1080/00401706.1965.10490297
State	Published - Jan 1 1965

All Science Journal Classification (ASJC) codes

Statistics and Probability
Modeling and Simulation
Applied Mathematics

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10.1080/00401706.1965.10490297

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abstract = "A general procedure is found for constructing good unbiased linear estimators of the location and scale parameters of a distribution for use with an uncensored sample of size n. It is presupposed that the coefficients of the best linear estimates are available for an uncensored sample of size m < n for the distribution under investigation. The coefficients of the proposed estimators are obtained as linear combinations of these with the aid of tabled values of the hypergeometric probability function.",

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The Construction of Good Linear Unbiased Estimates from the Best Linear Estimates for a Smaller Sample Size

Abstract

All Science Journal Classification (ASJC) codes

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