An asymptotic derivation of Neyman's C(α) test

Michael G. Akritas

doi:10.1016/0167-7152(88)90014-4

An asymptotic derivation of Neyman's C(α) test

Michael G. Akritas

Statistics

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Abstract

An idea of Chibisov (1969) for obtaining asymptotically optimal tests by solving a corresponding testing problem associated with the limiting Gaussian process is explored in the case of nuisance Eucledian parameters. It is shown that Neyman's C(α) test corresponds to the conditional test for the exponential family of the limiting Gaussian process. This sheds new insight into the nature of Neyman's projected scores. In addition the methodology helps suggest a one-step estimation procedure with nuisance Eucledian parameters.

Original language	English (US)
Pages (from-to)	363-367
Number of pages	5
Journal	Statistics and Probability Letters
Volume	6
Issue number	5
DOIs	https://doi.org/10.1016/0167-7152(88)90014-4
State	Published - Apr 1988

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/0167-7152(88)90014-4

Cite this

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An asymptotic derivation of Neyman's C(α) test

Abstract

All Science Journal Classification (ASJC) codes

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