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Applications of Measure Theory to Statistics (Paperback, Softcover reprint of the original 1st ed. 2016) Loot Price: R2,907
Discovery Miles 29 070
Applications of Measure Theory to Statistics (Paperback, Softcover reprint of the original 1st ed. 2016): Gogi Pantsulaia

Applications of Measure Theory to Statistics (Paperback, Softcover reprint of the original 1st ed. 2016)

Gogi Pantsulaia

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Loot Price R2,907 Discovery Miles 29 070 | Repayment Terms: R272 pm x 12*

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This book aims to put strong reasonable mathematical senses in notions of objectivity and subjectivity for consistent estimations in a Polish group by using the concept of Haar null sets in the corresponding group. This new approach - naturally dividing the class of all consistent estimates of an unknown parameter in a Polish group into disjoint classes of subjective and objective estimates - helps the reader to clarify some conjectures arising in the criticism of null hypothesis significance testing. The book also acquaints readers with the theory of infinite-dimensional Monte Carlo integration recently developed for estimation of the value of infinite-dimensional Riemann integrals over infinite-dimensional rectangles. The book is addressed both to graduate students and to researchers active in the fields of analysis, measure theory, and mathematical statistics.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Release date: April 2018
First published: 2016
Authors: Gogi Pantsulaia
Dimensions: 235 x 155 x 8mm (L x W x T)
Format: Paperback
Pages: 134
Edition: Softcover reprint of the original 1st ed. 2016
ISBN-13: 978-3-319-83322-4
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Science & Mathematics > Physics > General
Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Vector & tensor analysis
Books > Science & Mathematics > Mathematics > Topology > General
Books > Science & Mathematics > Mathematics > Applied mathematics > General
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LSN: 3-319-83322-7
Barcode: 9783319833224

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