Bertail P., Blanke D., Cornillon P.-A., Matzner-Lober E. (Eds.) Nonparametric Statistics: 3rd ISNPS, Avignon, France, June 2016

Springer, 2018. — 388 p. — (Springer Proceedings in Mathematics & Statistics 250). — ISBN: 978-3-319-96940-4.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 Avignon attracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge.Symmetrizing k-nn and Mutual k-nn Smoothers
Nonparametric PU Learning of State Estimation in Markov Switching Model
Multiplicative Bias Corrected Nonparametric Smoothers
Efficiency of the V -Fold Model Selection for Localized Bases
Non-parametric Lower Bounds and Information Functions
Modification of Moment-Based Tail Index Estimator: Sums Versus MAXIMA
Constructing Confidence Sets for the Matrix Completion Problem
A Nonparametric Classification Algorithm Based on Optimized Templates
PAC-Bayesian Aggregation of Affine Estimators
Light- and Heavy-Tailed Density Estimation by Gamma-Weibull Kernel
Adaptive Estimation of Heavy Tail Distributions with Application to Hall Model
Extremal Index for a Class of Heavy-Tailed Stochastic Processes in Risk Theory
Subsampling for Big Data: Some Recent Advances
Probability Bounds for Active Learning in the Regression Problem
Elemental Estimates, Influence, and Algorithmic Leveraging
Bootstrapping Nonparametric M-Smoothers with Independent Error Terms
Extension Sampling Designs for Big Networks: Application to Twitter
Wavelet Whittle Estimation in Multivariate Time Series Models: Application to fMRI Data
On Kernel Smoothing with Gaussian Subordinated Spatial Data
Strong Separability in Circulant SSA
Selection of Window Length in Singular Spectrum Analysis of a Time Series
Fourier-Type Monitoring Procedures for Strict Stationarity
Nonparametric and Parametric Methods for Change-Point Detection in Parametric Models
Variance Estimation Free Tests for Structural Changes in Regression
Bootstrapping Harris Recurrent Markov Chains