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Nonparametric Statistics (eBook)

4th ISNPS, Salerno, Italy, June 2018
eBook Download: PDF
2020 | 1st ed. 2020
X, 547 Seiten
Springer International Publishing (Verlag)
978-3-030-57306-5 (ISBN)

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Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics.

The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.




Michele La Rocca is a Full Professor of Statistics at the University of Salerno, Italy. He has published scientific papers on empirical likelihood, nonlinear time series and neural networks, resampling techniques, with applications to biological and financial data. He is an elected member of ISI and a former member of the Charting Committee of the International Society for Nonparametric Statistics.

Brunero Liseo has been a Full Professor of Statistics at the School of Economics, Sapienza University of Rome, Italy, since 2002. He has published more than 60 papers in international, peer-reviewed journals. His research interests include Bayesian inference, distribution theory, official statistics, and stochastic processes. He is the Director of the Ph.D. School of Economics, Sapienza, and a member of the Advisory Board of ISTAT, and of NADO Italia - the National Anti-Doping Organization, the Italian chapter of WADA.

Luigi Salmaso is a Full Professor of Statistics at the Department of Management and Engineering at the University of Padua, Italy. He is the author and creator of the NonParametric Combination Test software for multivariate and multistrata permutation tests. He has published more than 100 papers in international, peer-reviewed journals. His main research interests include nonparametric statistics, multivariate analysis, conjoint analysis, big data analytics, and biostatistics. He has received over 3000 citations and written a leading book on permutation testing. He is an Associate Editor for various international ISI journals. 


Erscheint lt. Verlag 11.11.2020
Reihe/Serie Springer Proceedings in Mathematics & Statistics
Springer Proceedings in Mathematics & Statistics
Zusatzinfo X, 547 p. 99 illus., 56 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Medizin / Pharmazie Allgemeines / Lexika
Wirtschaft
Schlagworte dependent data • joint modeling of longitudinal and time-to-event data • Nonparametric Curve Estimation • nonparametric estimation • nonparametric inference • Nonparametric Statistics • Ordinal Data • permutation and resampling techniques • rank-based methods for factorial design • regression smoothing • semiparametric statistics • Spatial Data • Survival Data • symmetry testing • Time Series • varying coefficient models
ISBN-10 3-030-57306-0 / 3030573060
ISBN-13 978-3-030-57306-5 / 9783030573065
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