A unified treatment of locally most powerful rank tests under type ii censoring

Gouri K. Bhattacharyya; Kishan G. Mehrotra

doi:10.1080/01621459.1983.10477980

A unified treatment of locally most powerful rank tests under type ii censoring

Gouri K. Bhattacharyya, Kishan G. Mehrotra

Department of Electrical Engineering & Computer Science

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

2 Scopus citations

Abstract

For the derivation of locally most powerful (LMP) rank tests, a general method that encompasses a wide variety of testing problems and type II censoring schemes is formulated. Applications are illustrated in the context of the one-sample, two-sample, and regression problems. It is shown that the traditional derivations of the LMP rank tests are greatly simplified with the proposed method. The LMP criterion is also applied to some problems for which only ad hoc tests were previously proposed.

Original language	English (US)
Pages (from-to)	375-381
Number of pages	7
Journal	Journal of the American Statistical Association
Volume	78
Issue number	382
DOIs	https://doi.org/10.1080/01621459.1983.10477980
State	Published - Jun 1983

Keywords

Censored data
Locally most powerful
Rank tests

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1080/01621459.1983.10477980

Cite this

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title = "A unified treatment of locally most powerful rank tests under type ii censoring",

abstract = "For the derivation of locally most powerful (LMP) rank tests, a general method that encompasses a wide variety of testing problems and type II censoring schemes is formulated. Applications are illustrated in the context of the one-sample, two-sample, and regression problems. It is shown that the traditional derivations of the LMP rank tests are greatly simplified with the proposed method. The LMP criterion is also applied to some problems for which only ad hoc tests were previously proposed.",

keywords = "Censored data, Locally most powerful, Rank tests",

author = "Bhattacharyya, {Gouri K.} and Mehrotra, {Kishan G.}",

note = "Funding Information: • Gouri K. Bhattacharyya is Professor, Department of Statistics, Univerity of Wisconsin, Madison, WI 53706. Kishan G. Mehrotra is Professor, School of Computer and Information Science, Syracuse University, Syracuse, NY 13210. This work was supported by Office of Naval Research Grant NOOO14-78-C-0722. The authors wish to thank the referees for valuable comments, which led to an improved presentation.",

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PY - 1983/6

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N2 - For the derivation of locally most powerful (LMP) rank tests, a general method that encompasses a wide variety of testing problems and type II censoring schemes is formulated. Applications are illustrated in the context of the one-sample, two-sample, and regression problems. It is shown that the traditional derivations of the LMP rank tests are greatly simplified with the proposed method. The LMP criterion is also applied to some problems for which only ad hoc tests were previously proposed.

AB - For the derivation of locally most powerful (LMP) rank tests, a general method that encompasses a wide variety of testing problems and type II censoring schemes is formulated. Applications are illustrated in the context of the one-sample, two-sample, and regression problems. It is shown that the traditional derivations of the LMP rank tests are greatly simplified with the proposed method. The LMP criterion is also applied to some problems for which only ad hoc tests were previously proposed.

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A unified treatment of locally most powerful rank tests under type ii censoring

Abstract

Keywords

ASJC Scopus subject areas

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