LEADER 05366nam 22006855 450 001 9910299774803321 005 20200705024247.0 010 $a3-319-18732-5 024 7 $a10.1007/978-3-319-18732-7 035 $a(CKB)3710000000422085 035 $a(EBL)2096825 035 $a(SSID)ssj0001525004 035 $a(PQKBManifestationID)11826342 035 $a(PQKBTitleCode)TC0001525004 035 $a(PQKBWorkID)11496973 035 $a(PQKB)10749937 035 $a(DE-He213)978-3-319-18732-7 035 $a(MiAaPQ)EBC2096825 035 $a(PPN)186400306 035 $a(EXLCZ)993710000000422085 100 $a20150604d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aModeling and Stochastic Learning for Forecasting in High Dimensions /$fedited by Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (344 p.) 225 1 $aLecture Notes in Statistics - Proceedings,$x1869-7240 ;$v217 300 $aDescription based upon print version of record. 311 $a3-319-18731-7 320 $aIncludes bibliographical references at the end of each chapters. 327 $a1 Short Term Load Forecasting in the Industry for Establishing Consumption Baselines: A French Case -- 2 Confidence intervals and tests for high-dimensional models: a compact review -- 3 Modelling and forecasting daily electricity load via curve linear regression -- 4 Constructing Graphical Models via the Focused Information Criterion -- 5 Nonparametric short term Forecasting electricity consumption with IBR -- 6 Forecasting the electricity consumption by aggregating experts -- 7 Flexible and dynamic modeling of dependencies via copulas -- 8 Operational and online residential baseline estimation -- 9 Forecasting intra day load curves using sparse functional regression -- 10 Modelling and Prediction of Time Series Arising on a Graph -- 11 GAM model based large scale electrical load simulation for smart grids -- 12 Spot volatility estimation for high-frequency data: adaptive estimation in practice -- 13 Time series prediction via aggregation: an oracle bound including numerical cost -- 14 Space-time trajectories of wind power generation: Parametrized precision matrices under a Gaussian copula approach -- 15 Game-theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts -- 16 The BAGIDIS distance: about a fractal topology, with applications to functional classification and prediction. 330 $aThe chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry. Forecasting and time series prediction have enjoyed considerable attention over the last few decades, fostered by impressive advances in observational capabilities and measurement procedures. On June 5-7, 2013, an international Workshop on Industry Practices for FORecasting was held in Paris, France, organized and supported by the OSIRIS Department of Electricité de France Research and Development Division. In keeping with tradition, both theoretical statistical results and practical contributions on this active field of statistical research and on forecasting issues in a rapidly evolving industrial environment are presented. The volume reflects the broad spectrum of the conference, including 16 articles contributed by specialists in various areas. The material compiled is broad in scope and ranges from new findings on forecasting in industry and in time series, on nonparametric and functional methods, and on on-line machine learning for forecasting, to the latest developments in tools for high dimension and complex data analysis. 410 0$aLecture Notes in Statistics - Proceedings,$x1869-7240 ;$v217 606 $aStatistics  606 $aMathematical models 606 $aMathematical statistics 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 615 0$aStatistics . 615 0$aMathematical models. 615 0$aMathematical statistics. 615 14$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aProbability and Statistics in Computer Science. 676 $a003.2 702 $aAntoniadis$b Anestis$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPoggi$b Jean-Michel$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBrossat$b Xavier$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299774803321 996 $aModeling and stochastic learning for forecasting in high dimensions$91522672 997 $aUNINA