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Time Series Analysis and Forecasting : Selected Contributions from the ITISE Conference / edited by Ignacio Rojas, Héctor Pomares.

Springer Nature - Springer Mathematics and Statistics eBooks 2016 English International Available online

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Format:
Book
Contributor:
Rojas, Ignacio., Editor.
Pomares, Héctor., Editor.
Series:
Contributions to Statistics, 2628-8966
Language:
English
Subjects (All):
Statistics.
Econometrics.
Computer science--Mathematics.
Computer science.
Mathematical statistics.
Statistics in Business, Management, Economics, Finance, Insurance.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Probability and Statistics in Computer Science.
Local Subjects:
Statistics in Business, Management, Economics, Finance, Insurance.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Econometrics.
Probability and Statistics in Computer Science.
Physical Description:
1 online resource (XIX, 384 p. 112 illus., 49 illus. in color.)
Edition:
1st ed. 2016.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2016.
Summary:
This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. 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.
Contents:
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.
Notes:
Includes bibliographical references.
ISBN:
3-319-28725-7

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