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ANOVA with dependent errors

Record Type:	Electronic resources : Monograph/item
Title/Author:	ANOVA with dependent errorsby Yuichi Goto ... [et al.].
other author:	Goto, Yuichi.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	xv, 91 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Analysis of variance.
Online resource:	https://doi.org/10.1007/978-981-99-4172-8
ISBN:	9789819941728$q(electronic bk.)

ANOVA with dependent errors
ANOVA with dependent errors[electronic resource] /by Yuichi Goto ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xv, 91 p. :ill., digital ;24 cm. - JSS research series in statistics,2364-0065. - JSS research series in statistics..

Introduction -- One-way fixed effects model -- One-way fixed effects model for high-dimensional time series -- One-way fixed and random effects models for correlated groups -- Two-way random effects model for correlated cells -- Optimal test for one-way random effects model -- Numerical analysis -- Empirical data analysis.

This book presents the latest results related to one- and two-way models for time series data. Analysis of variance (ANOVA) is a classical statistical method for IID data proposed by R.A. Fisher to investigate factors and interactions of phenomena. In contrast, the methods developed in this book apply to time series data. Testing theory of the homogeneity of groups is presented under a wide variety of situations including uncorrelated and correlated groups, fixed and random effects, multi- and high-dimension, parametric and nonparametric spectral densities. These methods have applications in several scientific fields. A test for the existence of interactions is also proposed. The book deals with asymptotics when the number of groups is fixed and sample size diverges. This framework distinguishes the approach of the book from panel data and longitudinal analyses, which mostly deal with cases in which the number of groups is large. The usefulness of the theory in this book is illustrated by numerical simulation and real data analysis. This book is suitable for theoretical statisticians and economists as well as psychologists and data analysts.

ISBN: 9789819941728$q(electronic bk.)

Standard No.: 10.1007/978-981-99-4172-8doiSubjects--Topical Terms:

181863
Analysis of variance.

LC Class. No.: QA279

Dewey Class. No.: 519.538

ANOVA with dependent errors
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490 1 $a JSS research series in statistics, $x 2364-0065
505 0 $a Introduction -- One-way fixed effects model -- One-way fixed effects model for high-dimensional time series -- One-way fixed and random effects models for correlated groups -- Two-way random effects model for correlated cells -- Optimal test for one-way random effects model -- Numerical analysis -- Empirical data analysis.
520 $a This book presents the latest results related to one- and two-way models for time series data. Analysis of variance (ANOVA) is a classical statistical method for IID data proposed by R.A. Fisher to investigate factors and interactions of phenomena. In contrast, the methods developed in this book apply to time series data. Testing theory of the homogeneity of groups is presented under a wide variety of situations including uncorrelated and correlated groups, fixed and random effects, multi- and high-dimension, parametric and nonparametric spectral densities. These methods have applications in several scientific fields. A test for the existence of interactions is also proposed. The book deals with asymptotics when the number of groups is fixed and sample size diverges. This framework distinguishes the approach of the book from panel data and longitudinal analyses, which mostly deal with cases in which the number of groups is large. The usefulness of the theory in this book is illustrated by numerical simulation and real data analysis. This book is suitable for theoretical statisticians and economists as well as psychologists and data analysts.
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650 2 4 $a Time Series Analysis. $3 913397
650 2 4 $a Multivariate Analysis. $3 239594
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950 $a Mathematics and Statistics (SpringerNature-11649)