Advances in Time Series Analysis and Forecasting
Springer International Publishing (Verlag)
978-3-319-55788-5 (ISBN)
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
research encompassing the disciplines of computer science, mathematics, statistics and econometrics.Ignacio Rojas is a full professor at the Department of Computer Architecture and Computer Technology, University of Granada, Spain. Throughout his research career, he has served as a principal investigator or participated in more than 20 research projects obtained in competitive calls including projects of the European Union, the I+D+I Spanish National Government and projects Excellence of the Ministry of Innovation, Science and Enterprise Junta de Andalucía. He has published more than 210 scientific contributions reflected in the database ISI Web of Knowledge, thereof 87 articles in JCR-indexed journals.
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.
| Erscheinungsdatum | 30.08.2017 |
|---|---|
| Reihe/Serie | Contributions to Statistics |
| Zusatzinfo | XV, 414 p. 112 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 805 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
| Wirtschaft ► Allgemeines / Lexika | |
| Schlagworte | 62-XX, 68-XX, 60-XX, 58-XX, 37-XX • 62-XX, 68-XX, 60-XX, 58-XX, 37-XX • advanced methods in time series • Big Data • Complex Data • Econometrics • econometrics & economic statistics • Econometrics & economic statistics • economics, finance, business & management • Economics, Finance, Business & Management • Forecasting • forecasting in real problems • high-dimensional data • irregularly sampled time series • linear and non-linear time series • Mathematical & statistical software • Mathematical & statistical software • mathematics and statistics • Maths for computer scientists • multi-scale analysis of time series • on-line learning in time series • probability & statistics • Probability and Statistics in Computer Science • Probability & statistics • Probability theory and stochastic processes • Science: general issues • Statistics for Business/Economics/Mathematical Fin • Statistics for Engineering, Physics, Computer Scie • stochastics • Time Series Analysis • Time Series Forecasting • univariate and multivariate time series |
| ISBN-10 | 3-319-55788-2 / 3319557882 |
| ISBN-13 | 978-3-319-55788-5 / 9783319557885 |
| Zustand | Neuware |
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