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＜電子ブック＞
Theory and Applications of Time Series Analysis and Forecasting : Selected Contributions from ITISE 2021 / edited by Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas
(Contributions to Statistics. ISSN:26288966)

版	1st ed. 2023.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2023
本文言語	英語
大きさ	XIII, 333 p. 1 illus : online resource
著者標目	Valenzuela, Olga editor Rojas, Fernando editor Herrera, Luis Javier editor Pomares, Héctor editor Rojas, Ignacio editor SpringerLink (Online service)
件　名	LCSH:Time-series analysis LCSH:Statistics  LCSH:Econometrics LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Mathematical statistics LCSH:Social sciences -- Mathematics  全ての件名で検索 LCSH:Data mining FREE:Time Series Analysis FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Econometrics FREE:Probability and Statistics in Computer Science FREE:Mathematics in Business, Economics and Finance FREE:Data Mining and Knowledge Discovery
一般注記	This book presents a selection of peer-reviewed contributions on the latest developments in time series analysis and forecasting, presented at the 7th International Conference on Time Series and Forecasting, ITISE 2021, held in Gran Canaria, Spain, July 19-21, 2021. It is divided into four parts. The first part addresses general modern methods and theoretical aspects of time series analysis and forecasting, while the remaining three parts focus on forecasting methods in econometrics, time series forecasting and prediction, and numerous other real-world applications. Covering a broad range of topics, the book will give readers a modern perspective on the subject. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics,statistics and econometrics. HTTP:URL=https://doi.org/10.1007/978-3-031-14197-3

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