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Nonparametric Statistics

3rd ISNPS, Avignon, France, June 2016

Pierre-André Cornillon (Hrsg.), Eric Matzner-Løber (Hrsg.), Patrice Bertail (Hrsg.), Delphine Blanke (Hrsg.)

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ca. 149,79 €
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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik

Beschreibung

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.


 

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Schlagwörter

Nonparametric statistics, Heavy-tailed distribution, High-dimensional data, Nonparametric smoother, Resampling, Survey sampling, Nonparametric inference, Statistical learning, Kernel methods, Time series, Big data, Dependent data, Machine learning