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Theory and Applications of Time Series Analysis

Selected Contributions from ITISE 2018

Héctor Pomares (Hrsg.), Olga Valenzuela (Hrsg.), Ignacio Rojas (Hrsg.), Fernando Rojas (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik

Beschreibung

This book presents selected peer-reviewed contributions from the International Conference on Time Series and Forecasting, ITISE 2018, held in Granada, Spain, on September 19-21, 2018. The first three parts of the book focus on the theory of time series analysis and forecasting, and discuss statistical methods, modern computational intelligence methodologies, econometric models, financial forecasting, and risk analysis. In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems. The book offers readers valuable insights into the different aspects of time series analysis and forecasting, allowing them to benefit both from its sophisticated and powerful theory, and from its practical applications, which address real-world problems in a range of disciplines.

The ITISE conference series provides avaluable forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.


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Schlagwörter

time series analysis, hierarchical forecasting, big and complex data, pattern recognition, econometrics forecasting, forecasting theory and adjustment, artificial intelligence, statistics for business, on-line learning in time series, computational intelligence methods for time series, high-dimensional data, risk analysis, energy time series forecasting, financial forecasting, time series in earth sciences