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Bootstrap methods = with application...

Dikta, Gerhard.

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Bootstrap methods = with applications in R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bootstrap methods/ by Gerhard Dikta, Marsel Scheer.
其他題名:	with applications in R /
作者:	Dikta, Gerhard.
其他作者:	Scheer, Marsel.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xvi, 256 p. :ill., digital ;24 cm.
內容註:	Introduction -- Generating random numbers -- The classical bootstrap -- Bootstrap based tests -- Regression analysis -- Goodness of fit test for generalized linear models -- boot package -- s i mTool package -- boot GOF package -- Session Info -- Notation and References -- Index.
Contained By:	Springer Nature eBook
標題:	Bootstrap (Statistics) - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-030-73480-0
ISBN:	9783030734800

Bootstrap methods = with applications in R /
Dikta, Gerhard.

Bootstrap methodswith applications in R /[electronic resource] :by Gerhard Dikta, Marsel Scheer. - Cham :Springer International Publishing :2021. - xvi, 256 p. :ill., digital ;24 cm.

Introduction -- Generating random numbers -- The classical bootstrap -- Bootstrap based tests -- Regression analysis -- Goodness of fit test for generalized linear models -- boot package -- s i mTool package -- boot GOF package -- Session Info -- Notation and References -- Index.

This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.

ISBN: 9783030734800

Standard No.: 10.1007/978-3-030-73480-0doiSubjects--Topical Terms:

3514691
Bootstrap (Statistics)
--Data processing.

LC Class. No.: QA276.8 / .D55 2021

Dewey Class. No.: 519.54

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