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

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

3 Scopus citations

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 - Jan 1 1988

All Science Journal Classification (ASJC) codes

Statistics, Probability and Uncertainty
Statistics and Probability

Access to Document

10.1016/0167-7152(88)90014-4

Cite this

@article{6d2a21ea3a3446b3b2ece6b81ca5efeb,

title = "An asymptotic derivation of Neyman's C(α) test",

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.",

author = "Akritas, {Michael G.}",

year = "1988",

month = jan,

day = "1",

doi = "10.1016/0167-7152(88)90014-4",

language = "English (US)",

volume = "6",

pages = "363--367",

journal = "Statistics and Probability Letters",

issn = "0167-7152",

publisher = "Elsevier",

number = "5",

}

TY - JOUR

T1 - An asymptotic derivation of Neyman's C(α) test

AU - Akritas, Michael G.

PY - 1988/1/1

Y1 - 1988/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=38249032059&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38249032059&partnerID=8YFLogxK

U2 - 10.1016/0167-7152(88)90014-4

DO - 10.1016/0167-7152(88)90014-4

M3 - Article

AN - SCOPUS:38249032059

VL - 6

SP - 363

EP - 367

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 5

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this