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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Modeling and Stochastic Learning for Forecasting in High Dimensions

Modeling and Stochastic Learning for Forecasting in High Dimensions

Antoniadis, Anestis
Poggi, Jean-Michel
Brossat, Xavier

Paperback

ApplicationsGeneral MathematicsProbability & Statistics

ISBN10: 3319187317
ISBN13: 9783319187310
Publisher: Springer
Published: Jun 25 2015
Pages: 339
Weight: 1.09
Height: 0.73 Width: 6.14 Depth: 9.21
Language: English
The chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry. Forecasting and time series prediction have enjoyed considerable attention over the last few decades, fostered by impressive advances in observational capabilities and measurement procedures. On June 5-7, 2013, an international Workshop on Industry Practices for Forecasting was held in Paris, France, organized and supported by the OSIRIS Department of Electricité de France Research and Development Division. In keeping with tradition, both theoretical statistical results and practical contributions on this active field of statistical research and on forecasting issues in a rapidly evolving industrial environment are presented. The volume reflects the broad spectrum of the conference, including 16 articles contributed by specialists in various areas. The material compiled is broad in scope and ranges from new findings on forecasting in industry and in time series, on nonparametric and functional methods and on on-line machine learning for forecasting, to the latest developments in tools for high dimension and complex data analysis.

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