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
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