Nonparametric Statistics, 1st ed. 2020
4th ISNPS, Salerno, Italy, June 2018
Springer Proceedings in Mathematics & Statistics Series, Vol. 339

Preface.- Portfolio optimisation via graphical least squares estimation (Saeed Aldahmani, Hongsheng Dai, Qiao-Zhen Zhang and Marialuisa Restaino).- Change of Measure Applications in Nonparametric Statistics (Mayer Alvo).- Choosing between weekly and monthly volatility drivers within a Double Asymmetric GARCH-MIDAS model (Alessandra Amendola, Vincenzo Candila and Giampiero M. Gallo).- Goodness-of-fit test for the baseline hazard rate (Anfriani, A. and Butucea, C. and Gerardin E. and Jeantheau, T. and Lecleire U.).- Permutation tests for multivariate stratified data: synchronized or unsynchronized permutations? (Rosa Arboretti, Eleonora Carrozzo and Luigi Salmaso).- An extension of the dgLARS method to high-dimensional relative risk regression models (Luigi Augugliaro, Ernst C. Wit and Angelo M. Mineo).- A kernel goodness-of-fit test for maximum likelihood density estimates of normal mixtures. (Dimitrios Bagkavos and Prakash N. Patil)- Robust estimation of sparse signal with unknown sparsity cluster value (Eduard Belitser, Nurzhan Nurushev, and Paulo Serra).- Test for sign effect in intertemporal choice experiments: a nonparametric solution (Stefano Bonnini and Isabel Maria Parra Oller).- Nonparametric first-order analysis of spatial and spatio-temporal point processes (M.I. Borrajo, I. Fuentes-Santos and W. González-Manteiga).- Bayesian nonparametric prediction with multi-sample data (Federico Camerlenghi, Antonio Lijoi and Igor Prünster).- Algorithm for Automatic Description of Historical Series of Forecast Error in Electrical Power Grid (Gaia Ceresa, Andrea Pitto, Diego Cirio and Nicolas Omont).- Linear wavelet estimation in regression with additive and multiplicative noise (Christophe Chesneau, Junke Kou and Fabien Navarro).- Speeding up algebraic-based sampling via permutations (Francesca Romana Crucinio and Roberto Fontana).- Obstacle Problems For Nonlocal Operators: A Brief Overview (Donatella Danielli, Arshak Petrosyan, and Camelia A. Pop).- Low and high resonance components restoration in multichannel data (Daniela De Canditiis and Italia De Feis).- Kernel circular deconvolution density estimation (Marco Di Marzio, Stefania Fensore, Agnese Panzera, Charles C. Taylor).- Asymptotic for Relative Frequency when Population is Driven by Arbitrary Unknown Evolution (Silvano Fiorin).- Semantic keywords clustering to optimize Text Ads campaigns (Pietro Fodra, Emmanuel Pasquet, Guillaume Mohr, Bruno Goutorbe, and Matthieu Cornec).- A Note on Robust Estimation of the Extremal Index (M. Ivette Gomes, Cristina Miranda and Manuela Souto de Miranda).- Multivariate permutation tests for ordered categorical data (Huiting Huang, Fortunato Pesarin, Rosa Arboretti, Riccardo Ceccato).- Smooth nonparametric survival analysis (Dimitrios Ioannides and Dimitrios Bagkavos).- Density estimation using multiscale local polynomial transforms (Maarten Jansen).- On Sensitivity of Metalearning: An Illustrative Study for Robust Regression (Jan Kalina).- Function-parametric empirical processes, projections and unitary operators (Estáte Khmaladze).- Rank-based Analysis of Multivariate Data in Factorial Designs and Its Implementation in R (Maximilian Kiefel and Arne C. Bathke).- Tests for Independence Involving Spherical Data (Pierre Lafaye de Micheaux, Simos Meintanis and Thomas Verdebout).- Interval-Wise Testing of Functional Data Defined on Two-dimensional Domains(Patrick B. Langthaler, Alessia Pini and Arne C. Bathke).- Assessing Data Support for the Simplifying Assumption in Bivariate Conditional Copulas (Evgeny Levi and Radu V. Craiu).- Semiparametric weighting estimations of a zero-inflated Poisson regression with missing in covariates (Lukusa, M.T. and Phoa, F.K.H.).- The Discrepancy Method for Extremal Index Estimation (Natalia Markovich).- Correction for optimisation bias in structured sparse high-dimensional variable selection (Bastien Marquis and Maarten Jansen).- United Statistical Algorithms and Data Science: An Introduction To The Principles (Subhadeep Mukhopadhyay).- The Halfspace Depth Characterization Problem (Stanislav Nagy).- A component multiplicative error model for realized volatility measures (Antonio Naimoli and Giuseppe Storti).- Asymptotically distribution-free goodness-of-fit tests for testing independence in contingency tables of large dimensions (Thuong T. M. Nguyen).- Incorporating model uncertainty in the construction of bootstrap prediction intervals for functional time series (Efstathios Paparoditis and Han Lin Shang).- Measuring and Estimating Overlap of Distributions: A comparison of approaches from various disciplines (Judith H. Parkinson and Arne C. Bathke).- Bootstrap confidence intervals for sequences of missing values in multivariate time series (Maria Lucia Parrella, Giuseppina Albano, Michele La Rocca and Cira Perna).- On Parametric Estimation of Distribution Tails (Igor Rodionov).- An empirical comparison of global and local functional depths (Carlo Sguera and Rosa E. Lillo).- AutoSpec: Detecting Exiguous Frequency Changes in Time Series (David S. Stoffer).- Bayesian quantile regression in differential equation models (Qianwen Tan and Subhashis Ghosal).- Predicting plant endemicity based on herbarium data: application to French data (Jessica Tressou, Thomas Haevermans and Liliane Bel).- Monte Carlo Permutation Tests for Assessing Spatial Dependence at Different Scales (Craig Wang and Reinhard Furrer).- Introduction to independent counterfactuals (Marcin Wolski).- The Potential for Nonparametric Joint Latent Class Modeling of Longitudinal and Time-to-Event Data (Ningshan Zhang and Jeffrey S. Simonoff).- To Rank or to Permute when Comparing an Ordinal Outcome Between Two Groups While Adjusting for a Covariate? (Georg Zimmermann).