KFU. Card publication. Numerical solution of Kiefer-Weiss problems when sampling from continuous exponential families

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FEDERAL UNIVERSITY

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NUMERICAL SOLUTION OF KIEFER-WEISS PROBLEMS WHEN SAMPLING FROM CONTINUOUS EXPONENTIAL FAMILIES

Form of presentation

Articles in international journals and collections

Year of publication

2023

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Authors, employees of KFU

Novikov Andrey Andreevich, author

Other authors

Novikov Andrey Alekseevich, author

Authors, students KFU

Farkhshatov Fail Railevich, author

Bibliographic description in the original language

A Novikov, A Novikov, F Farkhshatov Numerical solution of Kiefer-Weiss problems when sampling from continuous exponential families Sequential Analysis 42 (2), 189-209

Annotation

In this article, we deal with problems of testing hypotheses in the framework of sequential statistical analysis. The main concern is the optimal design and performance evaluation of sampling plans in Kiefer-Weiss problems. The main goal of the Kiefer-Weiss problem is designing hypothesis tests that minimize the maximum average sample number, over all parameter values, as opposed to both the sequential probability tests (SPRTs) minimizing the average sample number only at two hypothesis points and the classical fixed-sample-size test. For observations that follow a distribution from an exponential family of the continuous type, we provide algorithms for optimal design in the modified Kiefer-Weiss problem and obtain formulas for evaluating the performance of sequential tests by calculating the operating characteristic function, the average sample number, and some related characteristics.

Keywords

sequential analysis; hypothesis testing; optimal stopping; optimal sequential tests; Kiefer-Weiss problem; exponential family

The name of the journal

Sequential Analysis

URL

https://www.tandfonline.com/doi/abs/10.1080/07474946.2023.2193602

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=316733&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Novikov Andrey Andreevich	ru_RU
dc.contributor.author	Novikov Andrey Alekseevich	ru_RU
dc.contributor.author	Farkhshatov Fail Railevich	ru_RU
dc.date.accessioned	2023-01-01T00:00:00Z	ru_RU
dc.date.available	2023-01-01T00:00:00Z	ru_RU
dc.date.issued	2023	ru_RU
dc.identifier.citation	A Novikov, A Novikov, F Farkhshatov Numerical solution of Kiefer-Weiss problems when sampling from continuous exponential families Sequential Analysis 42 (2), 189-209	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=316733&p_lang=2	ru_RU
dc.description.abstract	Sequential Analysis	ru_RU
dc.description.abstract	In this article, we deal with problems of testing hypotheses in the framework of sequential statistical analysis. The main concern is the optimal design and performance evaluation of sampling plans in Kiefer-Weiss problems. The main goal of the Kiefer-Weiss problem is designing hypothesis tests that minimize the maximum average sample number, over all parameter values, as opposed to both the sequential probability tests (SPRTs) minimizing the average sample number only at two hypothesis points and the classical fixed-sample-size test. For observations that follow a distribution from an exponential family of the continuous type, we provide algorithms for optimal design in the modified Kiefer-Weiss problem and obtain formulas for evaluating the performance of sequential tests by calculating the operating characteristic function, the average sample number, and some related characteristics.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Numerical solution of Kiefer-Weiss problems when sampling from continuous exponential families	ru_RU
dc.type	Articles in international journals and collections	ru_RU