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Titlebook: Nonparametric Statistics; 3rd ISNPS, Avignon, Patrice Bertail,Delphine Blanke,Eric Matzner-L?ber Conference proceedings 2018 Springer Natu

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書目名稱Nonparametric Statistics
副標題3rd ISNPS, Avignon,
編輯Patrice Bertail,Delphine Blanke,Eric Matzner-L?ber
視頻videohttp://file.papertrans.cn/668/667832/667832.mp4
概述Updates the reader on cutting-edge research in nonparametric statistics.Features the latest findings on high-dimensional data, machine learning, data mining, big data and resampling methods, as well a
叢書名稱Springer Proceedings in Mathematics & Statistics
圖書封面Titlebook: Nonparametric Statistics; 3rd ISNPS, Avignon,  Patrice Bertail,Delphine Blanke,Eric Matzner-L?ber Conference proceedings 2018 Springer Natu
描述.This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data.? . .The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignonattracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge..?.
出版日期Conference proceedings 2018
關鍵詞Nonparametric statistics; Time series; Statistical learning; Kernel methods; Resampling; Big data; Survey
版次1
doihttps://doi.org/10.1007/978-3-319-96941-1
isbn_ebook978-3-319-96941-1Series ISSN 2194-1009 Series E-ISSN 2194-1017
issn_series 2194-1009
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Patrice Bertail,Delphine Blanke,Eric Matzner-L?berUpdates the reader on cutting-edge research in nonparametric statistics.Features the latest findings on high-dimensional data, machine learning, data mining, big data and resampling methods, as well a
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PAC-Bayesian Aggregation of Affine Estimators,verpenalization to obtain oracle inequality in probability for such an explicit aggregation procedure. We focus on the fixed design regression framework and the aggregation of linear estimators and obtain results for a large family of linear estimators under a non-necessarily independent sub-Gaussian noise assumptions.
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Springer Proceedings in Mathematics & Statisticshttp://image.papertrans.cn/n/image/667832.jpg
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D. N. Politis,V. A. Vasiliev,S. E. Vorobeychikovnd 262 references.This text is appropriate for a one-semester graduate course in lattice theory, and it will also serve as a valuable reference for researchers studying lattices.?.Reviews of previous editi978-3-031-29065-7978-3-031-29063-3
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