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Handbook of Bayesian, fiducial, and frequentist inference /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Handbook of Bayesian, fiducial, and frequentist inference /edited by James Berger ... [et al.].
other author:	Berger, James,
Published:	Boca Raton, FL :CRC Press/Taylor & Francis Group,2024.
Description:	xiii, 405 p. :ill. ;27 cm.
Subject:	Statistical decisionTextbooks.
ISBN:	9780367321987 :

Handbook of Bayesian, fiducial, and frequentist inference /
Handbook of Bayesian, fiducial, and frequentist inference /edited by James Berger ... [et al.]. - 1st ed. - Boca Raton, FL :CRC Press/Taylor & Francis Group,2024. - xiii, 405 p. :ill. ;27 cm. - Chapman & Hall/CRC handbooks of modern statistical methods. - Chapman & Hall/CRC handbooks of modern statistical methods..

Includes bibliographical references and index.

"The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference"--

ISBN: 9780367321987 :NT$6105

LCCN: 2023037656Subjects--Topical Terms:

829165
Statistical decision
--Textbooks.

LC Class. No.: QA279.4 / .H348 2024

Dewey Class. No.: 519.5/42

Handbook of Bayesian, fiducial, and frequentist inference /
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020 $a 9780367321987 : $c NT$6105
020 $a 9781032684581 (pbk.)
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050 0 0 $a QA279.4 $b .H348 2024
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245 0 0 $a Handbook of Bayesian, fiducial, and frequentist inference / $c edited by James Berger ... [et al.].
250 $a 1st ed.
260 $a Boca Raton, FL : $b CRC Press/Taylor & Francis Group, $c 2024.
300 $a xiii, 405 p. : $b ill. ; $c 27 cm.
490 1 $a Chapman & Hall/CRC handbooks of modern statistical methods
504 $a Includes bibliographical references and index.
520 $a "The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference"-- $c Provided by publisher.
650 0 $a Statistical decision $v Textbooks. $3 829165
650 0 $a Bayesian statistical decision theory $v Textbooks. $3 443102
700 1 $a Berger, James, $e editor. $3 1011709
830 0 $a Chapman & Hall/CRC handbooks of modern statistical methods. $3 507067