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＜電子ブック＞
Advances in Time Series Analysis and Forecasting : Selected Contributions from ITISE 2016 / edited by Ignacio Rojas, Héctor Pomares, Olga Valenzuela
(Contributions to Statistics. ISSN:26288966)

版	1st ed. 2017.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2017
本文言語	英語
大きさ	XV, 414 p. 112 illus : online resource
著者標目	Rojas, Ignacio editor Pomares, Héctor editor Valenzuela, Olga editor SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Econometrics LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Mathematical statistics LCSH:Probabilities FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Econometrics FREE:Probability and Statistics in Computer Science FREE:Probability Theory FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
一般注記	Preface -- Part I: Analysis of Irregularly Sampled Time Series: Techniques, Algorithms and Case Studies -- Scientific Contributions -- Part II: Multi-scale Analysis of Univariate and Multivariate Time Series -- Scientific Contributions -- Part III: Linear and Non-linear Time Series Models -- Scientific Contributions -- Part IV: Advanced Time Series Forecasting Methods -- Scientific Contributions -- Part V: Applications in Time Series Analysis and Forecasting -- Scientific Contributions -- Author Index This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of computer science, mathematics, statistics and econometrics HTTP:URL=https://doi.org/10.1007/978-3-319-55789-2

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