ANOVA with Dependent Errors (1st ed. 2023)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	JSS Research Series in Statistics
Release date:	July 2023
First published:	2023
Authors:	Yuichi Goto • Hideaki Nagahata • Masanobu Taniguchi • Anna Clara Monti • Xiaofei Xu
Dimensions:	235 x 155mm (L x W)
Pages:	91
Edition:	1st ed. 2023
ISBN-13:	978-981-9941-71-1
Categories:	Books
LSN:	981-9941-71-7
Barcode:	9789819941711

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