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Titlebook: Modeling and Stochastic Learning for Forecasting in High Dimensions; Anestis Antoniadis,Jean-Michel Poggi,Xavier Brossa Conference proceed

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發(fā)表于 2025-3-21 17:49:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Modeling and Stochastic Learning for Forecasting in High Dimensions
編輯Anestis Antoniadis,Jean-Michel Poggi,Xavier Brossa
視頻videohttp://file.papertrans.cn/637/636196/636196.mp4
概述Presents contributions from the International Workshop on Industry Practices for Forecasting (June 5-7, 2013, Paris, France).Shows latest developments in forecasting and time series prediction.Include
叢書名稱Lecture Notes in Statistics
圖書封面Titlebook: Modeling and Stochastic Learning for Forecasting in High Dimensions;  Anestis Antoniadis,Jean-Michel Poggi,Xavier Brossa Conference proceed
描述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 co
出版日期Conference proceedings 2015
關(guān)鍵詞Copulas; forecasting; high dimensional statistics; multiscale processes; time series
版次1
doihttps://doi.org/10.1007/978-3-319-18732-7
isbn_softcover978-3-319-18731-0
isbn_ebook978-3-319-18732-7Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Anestis Antoniadis,Jean-Michel Poggi,Xavier BrossaPresents contributions from the International Workshop on Industry Practices for Forecasting (June 5-7, 2013, Paris, France).Shows latest developments in forecasting and time series prediction.Include
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Conference proceedings 2015 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 co
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Modeling and Stochastic Learning for Forecasting in High Dimensions
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0930-0325 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 co978-3-319-18731-0978-3-319-18732-7Series ISSN 0930-0325 Series E-ISSN 2197-7186
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0930-0325 velopments in forecasting and time series prediction.IncludeThe 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
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