Robust And Multivariate Statistical Methods Festschrift In

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Robust And Multivariate Statistical Methods

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Author : Mengxi Yi
language : en
Publisher: Springer Nature
Release Date : 2023-04-19

Robust And Multivariate Statistical Methods written by Mengxi Yi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Mathematics categories.

This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.

Modern Nonparametric Robust And Multivariate Methods

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Author : Klaus Nordhausen
language : en
Publisher: Springer
Release Date : 2015-10-05

Modern Nonparametric Robust And Multivariate Methods written by Klaus Nordhausen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-05 with Mathematics categories.

Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

Robustness And Complex Data Structures

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Author : Claudia Becker
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-07-08

Robustness And Complex Data Structures written by Claudia Becker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-08 with Mathematics categories.

​This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.

Robust Statistics Data Analysis And Computer Intensive Methods

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Author : Helmut Rieder
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Robust Statistics Data Analysis And Computer Intensive Methods written by Helmut Rieder and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

To celebrate Peter Huber's 60th birthday in 1994, our university had invited for a festive occasion in the afternoon of Thursday, June 9. The invitation to honour this outstanding personality was followed by about fifty colleagues and former students from, mainly, allover the world. Others, who could not attend, sent their congratulations by mail and e-mail (P. Bickel:" ... It's hard to imagine that Peter turned 60 ... "). After a welcome address by Adalbert Kerber (dean), the following lectures were delivered. Volker Strassen (Konstanz): Almost Sure Primes and Cryptography -an Introduction Frank Hampel (Zurich): On the Philosophical Foundations of Statistics 1 Andreas Buja (Murray Hill): Projections and Sections High-Dimensional Graphics for Data Analysis. The distinguished speakers lauded Peter Huber a hard and fair mathematician, a cooperative and stimulating colleague, and an inspiring and helpful teacher. The Festkolloquium was surrounded with a musical program by the Univer 2 sity's Brass Ensemble. The subsequent Workshop "Robust Statistics, Data Analysis and Computer Intensive Methods" in Schloss Thurnau, Friday until Sunday, June 9-12, was organized about the areas in statistics that Peter Huber himself has markedly shaped. In the time since the conference, most of the contributions could be edited for this volume-a late birthday present-that may give a new impetus to further research in these fields.

Robust Multivariate Analysis

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Author : David J. Olive
language : en
Publisher: Springer
Release Date : 2017-11-28

Robust Multivariate Analysis written by David J. Olive and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-28 with Mathematics categories.

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.

Robust Rank Based And Nonparametric Methods

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Author : Regina Y. Liu
language : en
Publisher: Springer
Release Date : 2016-09-20

Robust Rank Based And Nonparametric Methods written by Regina Y. Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-20 with Mathematics categories.

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

Frontiers In Statistics

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Author : Jianqing Fan
language : en
Publisher: World Scientific
Release Date : 2006-07-17

Frontiers In Statistics written by Jianqing Fan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-17 with Mathematics categories.

During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel's distinguished contributions.

Special Issue On Robust Multivariate Analysis And Classification

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Author : Marco Riani
language : en
Publisher:
Release Date : 2006

Special Issue On Robust Multivariate Analysis And Classification written by Marco Riani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.

Nonparametric Statistical Methods And Related Topics

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Author : Francisco J. Samaniego
language : en
Publisher: World Scientific
Release Date : 2011

Nonparametric Statistical Methods And Related Topics written by Francisco J. Samaniego and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Mathematics categories.

Review papers. 1. On the scholarly work of P.K. Bhattacharya / P. Hall and F.J. Samaniego. 2. The propensity score and its role in causal inference / C. Drake and T. Loux. 3. Recent tests for symmetry with multivariate and structured data: a review / S.G. Meintanis and J. Ngatchou-Wandji -- Papers on general nonparametric inference. 4. On robust versions of classical tests with dependent data / J. Jiang. 5. Density estimation by sampling from stationary continuous time parameter associated processes / G.G. Roussas and D. Bhattacharya. 6. A Short proof of the Feigin-Tweedie theorem on the existence of the mean functional of a Dirichlet process / J. Sethuraman. 7. Max-min Bernstein polynomial estimation of a discontinuity in distribution / K.-S. Song. 8. U-statistics based on higher-order spacings / D.D. Tung and S.R. Jammalamadaka. 9. Nonparametric models for non-Gaussian longitudinal data / N. Zhang, H.-G. Muller and J.-L. Wang -- Papers on aspects of linear or generalized linear models. 10. Better residuals / R. Beran. 11. The use of Peters-Belson regression in legal cases / E. Bura, J.L. Gastwirth and H. Hikawa. 12. On a hybrid approach to parametric and nonparametric regression / P. Burman and P. Chaudhuri. 13. Nonparametric regression models with integrated covariates / Z. Cai. 14. A dynamic test for misspecification of a linear model / M.P. McAssey and F. Hsieh. 15. The principal component decomposition of the basic martingale / W. Stute -- Papers on time series analysis. 16. Fast scatterplot smoothing using blockwise least squares fitting / A. Aue and T.C.M. Lee. 17. Some recent advances in semiparametric estimation of the GARCH model / J. Di and A. Gangopadhyay. 18. Extreme dependence in multivariate time series: a review / R. Sen and Z. Tan. 19. Dynamic mixed models for irregularly observed water quality data / R.H. Shumway -- Papers on asymptotic theory. 20. Asymptotic behavior of the kernel density estimators for nonstationary dependent random variables with binned data / J.-F. Lenain, M. Harel and M.L. Puri. 21. Convergence rates of an improved isotonic regression estimator / H. Mukerjee. 22. Asymptotic distribution of the smallest eigenvalue of Wishart(N, n) When N, n ' [symbol] such that N/n --> 0 / D. Paul

Innovations In Multivariate Statistical Analysis

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Author : Risto D.H. Heijmans
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Innovations In Multivariate Statistical Analysis written by Risto D.H. Heijmans and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.

The three decades which have followed the publication of Heinz Neudecker's seminal paper `Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products' in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines. Amongst these are the disciplines to which Neudecker has contributed directly - namely econometrics, economics, psychometrics and multivariate analysis. This book aims to illustrate how powerful the tools of matrix analysis have become as weapons in the statistician's armoury. The majority of its chapters are concerned primarily with theoretical innovations, but all of them have applications in view, and some of them contain extensive illustrations of the applied techniques. This book will provide research workers and graduate students with a cross-section of innovative work in the fields of matrix methods and multivariate statistical analysis. It should be of interest to students and practitioners in a wide range of subjects which rely upon modern methods of statistical analysis. The contributors to the book are themselves practitioners of a wide range of subjects including econometrics, psychometrics, educational statistics, computation methods and electrical engineering, but they find a common ground in the methods which are represented in the book. It is envisaged that the book will serve as an important work of reference and as a source of inspiration for some years to come.