---

＜電子ブック＞
ANOVA with Dependent Errors / by Yuichi Goto, Hideaki Nagahata, Masanobu Taniguchi, Anna Clara Monti, Xiaofei Xu
(JSS Research Series in Statistics. ISSN:23640065)

版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
本文言語	英語
大きさ	XV, 91 p. 17 illus., 13 illus. in color : online resource
著者標目	*Goto, Yuichi author Nagahata, Hideaki author Taniguchi, Masanobu author Monti, Anna Clara author Xu, Xiaofei author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Time-series analysis LCSH:Multivariate analysis FREE:Applied Statistics FREE:Statistical Theory and Methods FREE:Time Series Analysis FREE:Multivariate Analysis
一般注記	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 illustratedby numerical simulation and real data analysis. This book is suitable for theoretical statisticians and economists as well as psychologists and data analysts HTTP:URL=https://doi.org/10.1007/978-981-99-4172-8

 類似資料