03702nam0 2200529 i 450 VAN0011360720260701115211.489N978331918732793413350720180115d2015 |0itac50 baengCH|||| |||||i e bcrModeling and stochastic learning for forecasting in high dimensionsAnestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors[Cham]Springer2015X, 339 p.ill.24 cmThe 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.001VAN000019572001 Lecture notes in statistics210 New York [etc.]Springer1980-217001VAN001142742001 Lecture notes in statistics. Proceedings210 Berlin [etc.]SpringerVAN00235142Modeling and stochastic learning for forecasting in high dimensions152267200A69General applied mathematics [MSC 2020]VANC022597MF00B25Proceedings of conferences of miscellaneous specific interest [MSC 2020]VANC020732MF62-XXStatistics [MSC 2020]VANC022998MF62M10Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020]VANC025079MF62P30Applications of statistics in engineering and industry; control charts [MSC 2020]VANC030774MFCopulasKW:KForecastingKW:KHigh-dimensional statisticsKW:KMultiscale processesKW:KTime seriesKW:KCHChamVANL001889AntoniadisAnestisVANV087689BrossatXavierVANV087691PoggiJean-MichelVANV087690Springer <editore>VANV108073650Antoniadis, A.Antoniadis, AnestisVANV274826ITSOL20260911RICAhttp://dx.doi.org/10.1007/978-3-319-18732-7E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN00113607BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08DLOAD e-book 0326 08eMF326 20180115 Modeling and stochastic learning for forecasting in high dimensions1522672UNICAMPANIA