Time series analysis and forecasting : selected contributions from the ITISE Conference /

Time series analysis and forecasting : selected contributions from the ITISE Conference /

Saved in:

Bibliographic Details
Imprint:	Switzerland : Springer, 2016.
Description:	1 online resource (xix, 384 pages) : illustrations (some color)
Language:	English
Series:	Contributions to statistics, 1431-1968 Contributions to statistics.
Subject:	Time-series analysis -- Congresses. Time-series analysis. Electronic books. Conference papers and proceedings.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11263198

Hidden Bibliographic Details
Other authors / contributors:	Rojas, Ignacio, editor. Pomares, Héctor, editor. International Work-Conference on Time Series (2015 : Granada, Spain)
ISBN:	9783319287256 3319287257 9783319287232
Notes:	Includes bibliographical references. Online resource; title from PDF title page (SpringerLink, viewed June 14, 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.
Other form:	Print version: Rojas, Ignacio. Time Series Analysis and Forecasting : Selected Contributions from the ITISE Conference. Cham : Springer International Publishing, ©2016 9783319287232
Standard no.:	10.1007/978-3-319-28725-6

Table of 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.