LEADER 06246nam 22005655 450 001 9910315360203321 005 20200705070550.0 010 $a3-319-96941-2 024 7 $a10.1007/978-3-319-96941-1 035 $a(CKB)4100000007761867 035 $a(MiAaPQ)EBC5726267 035 $a(DE-He213)978-3-319-96941-1 035 $a(PPN)235228893 035 $a(EXLCZ)994100000007761867 100 $a20190308d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNonparametric Statistics $e3rd ISNPS, Avignon, France, June 2016 /$fedited by Patrice Bertail, Delphine Blanke, Pierre-André Cornillon, Eric Matzner-Løber 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (388 pages) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v250 311 $a3-319-96940-4 327 $aSymmetrizing k-nn and Mutual k-nn Smoothers (P. A. Cornillon, A. Gribinski, N. Hengartner, T. Kerdreux and E. Matzner-Løber) -- Multiplicative Bias Corrected Nonparametric Smoothers (N. Hengartner, E. Matzner-Løber, L. Rouvière and T. Burr) -- Nonparametric PU Learning of State Estimation in Markov Switching Model (A. Dobrovidov and V. Vasilyev) -- Nonparametric Lower Bounds and Information Functions (S. Y. Novak) -- Efficiency of the V-fold Model Selection for Localized Bases (F. Navarro and A. Saumard) -- Modification of Moment-based Tail Index Estimator: Sums versus Maxima (N. Markovich and M. Vai?iulis) -- Constructing Confidence Sets for the Matrix Completion Problem (A. Carpentier, O. Klopp and M. Löffler) -- PAC-Bayesian Aggregation of Affine Estimators (L. Montuelle and E. Le Pennec) -- A Nonparametric Classification Algorithm Based on Optimized Templates (J. Kalina) -- Light- and Heavy-tailed Density Estimation by Gamma-Weibull Kernel (L. Markovich) -- Adaptive Estimation of Heavy Tail Distributions with Application to Hall Model (D. N. Politis, V. A. Vasiliev, S. E. Vorobeychikov) -- Extremal Index for a Class of Heavy-tailed Stochastic Processes in Risk Theory (C. Tillier) -- Elemental Estimates, Influence, and Algorithmic Leveraging (K. Knight) -- Bootstrapping Nonparametric M-Smoothers with Independent Error Terms (M. Maciak) -- Probability Bounds for Active Learning in the Regression Problem (A. K. Fermin and C. Ludeña) -- Subsampling for Big Data: Some Recent Advances (P. Bertail, O. Jelassi, J. Tressou and M. Zetlaoui) -- Extension Sampling Designs for Big Networks: Application to Twitter (A. Rebecq) -- Strong Separability in Circulant SSA (J. Bógalo, P. Poncela and E. Senra) -- Selection of Window Length in Singular Spectrum Analysis of a Time Series (P. Unnikrishnan and V. Jothiprakash) -- Fourier-type Monitoring Procedures for Strict Stationarity (S. Lee, S. G. Meintanis and C. Pretorius) -- Wavelet Whittle Estimation in Multivariate Time Series Models: Application to fMRI Data (S. Achard and I. Gannaz) -- On Kernel Smoothing with Gaussian Subordinated Spatial Data (S. Ghosh) -- Nonparametric and Parametric Methods for Change-Point Detection in Parametric Models (G. Ciuperca) -- Variance Estimation Free Tests for Structural Changes in Regression (B. Pe?tová and M. Pe?ta) -- Index. 330 $aThis volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignon attracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge. 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v250 606 $aStatistics  606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 615 0$aStatistics . 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing/Statistics Programs. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aStatistics for Business, Management, Economics, Finance, Insurance. 615 24$aStatistics for Life Sciences, Medicine, Health Sciences. 676 $a519.54 702 $aBertail$b Patrice$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBlanke$b Delphine$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCornillon$b Pierre-André$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMatzner-Løber$b Eric$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910315360203321 996 $aNonparametric Statistics$9455736 997 $aUNINA