Diagnostic methods in time series / Fumiya Akashi, Masanobu Taniguchi, Anna Clara Monti, Tomoyuki Amano.
2021
QA280 .A43 2021
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Title
Diagnostic methods in time series / Fumiya Akashi, Masanobu Taniguchi, Anna Clara Monti, Tomoyuki Amano.
Author
ISBN
9789811622649 (electronic book)
9811622647 (electronic book)
9789811622632 (paperback)
9811622639 (paperback)
9811622647 (electronic book)
9789811622632 (paperback)
9811622639 (paperback)
Published
Singapore : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (x, 108 pages) : illustrations (some color).
Item Number
10.1007/978-981-16-2264-9 doi
Call Number
QA280 .A43 2021
Dewey Decimal Classification
519.5/5
Summary
This book contains new aspects of model diagnostics in time series analysis, including variable selection problems and higher-order asymptotics of tests. This is the first book to cover systematic approaches and widely applicable results for nonstandard models including infinite variance processes. The book begins by introducing a unified view of a portmanteau-type test based on a likelihood ratio test, useful to test general parametric hypotheses inherent in statistical models. The conditions for the limit distribution of portmanteau-type tests to be asymptotically pivotal are given under general settings, and very clear implications for the relationships between the parameter of interest and the nuisance parameter are elucidated in terms of Fisher-information matrices. A robust testing procedure against heavy-tailed time series models is also constructed in the context of variable selection problems. The setting is very reasonable in the context of financial data analysis and econometrics, and the result is applicable to causality tests of heavy-tailed time series models. In the last two sections, Bartlett-type adjustments for a class of test statistics are discussed when the parameter of interest is on the boundary of the parameter space. A nonlinear adjustment procedure is proposed for a broad range of test statistics including the likelihood ratio, Wald and score statistics.-- Provided by publisher.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Historical Data
Fumiya Akashi is an Assistant Professor in the Faculty of Economics at the University of Tokyo. Masanobu Taniguchi is a Professor in the Research Institute for Science and Engineering at Waseda University. Anna Clara Monti is a Professor in the Department of Law, Economics, Management and Quantitative Methods at University of Sannio. Tomoyuki Amano is an Associate Professor in Division of General Education at The University of Electro-Communications.
Source of Description
Description based on print version record.
Series
SpringerBriefs in statistics. JSS research series in statistics.
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Table of Contents
1. Elements of stochastic processes
2. Systematic approach for portmanteau tests
3. A new look at portmanteau test
4. Adjustments for a class of tests under nonstandard conditions
5. Adjustments for variance component tests in ANOVA models
6. Robust causality test of infinite variance processes.
2. Systematic approach for portmanteau tests
3. A new look at portmanteau test
4. Adjustments for a class of tests under nonstandard conditions
5. Adjustments for variance component tests in ANOVA models
6. Robust causality test of infinite variance processes.