Time Series Analysis and Forecasting
Springer International Publishing (Verlag)
978-3-319-28723-2 (ISBN)
The International Work-Conferences on Time Series (ITISE) provide 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 and Director of the Information and Communications Technology Centre (CITIC-UGR), 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 204 scientific contributions reflected in the database ISI Web of Science, thereof 85 articles in JCR-indexed journals. Héctor Pomares has been a full professor at the University of Granada in Spain since 2001. He has published more than 50 articles in JCR-indexed journals and contributed with more than 150 papers in international conferences. He has led or participated in 15 national projects, one autonomic R&D Excellence project and 13 contracts signed for innovative research through the University of Granada Foundation Company and the Office of Transfer of Research Results. He is a member of the editorial board of the Journal of Applied Mathematics (JCR-indexed) and is the coordinator of the Official Master's Degree in Computer & Network Engineering at the University of Granada.
Main Topics:
Time Series Analysis and Forecasting.- Advanced method and on-Line Learning in time series.- High Dimension and Complex/Big Data.- Forecasting in real problem.
Erscheinungsdatum | 13.06.2016 |
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Reihe/Serie | Contributions to Statistics |
Zusatzinfo | XIX, 384 p. 112 illus., 49 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
Wirtschaft ► Allgemeines / Lexika | |
Schlagworte | 37M10, 62M10, 62-XX, 68-XX, 60-XX, 58-XX, 37-XX • applications in computer science • applications in econometrics • applications in industry • Big Data • Econometrics • Forecasting • high-dimensional data • machine learning • mathematics and statistics • on-line learning • Probability and Statistics in Computer Science • real-life problems • statistical methods for time series • Statistics for Business/Economics/Mathematical Fin • Statistics for Engineering, Physics, Computer Scie • Time Series Analysis |
ISBN-10 | 3-319-28723-0 / 3319287230 |
ISBN-13 | 978-3-319-28723-2 / 9783319287232 |
Zustand | Neuware |
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