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＜電子ブック＞
Bootstrap Methods : With Applications in R / by Gerhard Dikta, Marsel Scheer

版	1st ed. 2021.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2021
大きさ	XVI, 256 p. 36 illus., 29 illus. in color : online resource
著者標目	*Dikta, Gerhard author Scheer, Marsel author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Biometry LCSH:Bioinformatics FREE:Statistical Theory and Methods FREE:Biostatistics FREE:Bioinformatics
一般注記	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 HTTP:URL=https://doi.org/10.1007/978-3-030-73480-0

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