Robust Statistics Data Analysis And Computer Intensive Methods

Author : Helmut Rieder
Publisher : Springer Science & Business Media
Page : 439 pages
File Size : 54,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461223801

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Robust Statistics, Data Analysis, and Computer Intensive Methods by Helmut Rieder Pdf

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.

Author : Helmut Rieder
Publisher : Unknown
Page : 452 pages
File Size : 40,5 Mb
Release : 1995-12-22
Category : Electronic
ISBN : 1461223814

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Robust Statistics, Data Analysis, and Computer Intensive Methods by Helmut Rieder Pdf

Author : Silvelyn Zwanzig,Behrang Mahjani
Publisher : CRC Press
Page : 227 pages
File Size : 45,7 Mb
Release : 2019-11-27
Category : Business & Economics
ISBN : 9780429510946

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Computer Intensive Methods in Statistics by Silvelyn Zwanzig,Behrang Mahjani Pdf

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment. Computer Intensive Methods in Statistics is written for students at graduate level, but can also be used by practitioners. Features Presents the main ideas of computer-intensive statistical methods Gives the algorithms for all the methods Uses various plots and illustrations for explaining the main ideas Features the theoretical backgrounds of the main methods. Includes R codes for the methods and examples Silvelyn Zwanzig is an Associate Professor for Mathematical Statistics at Uppsala University. She studied Mathematics at the Humboldt- University in Berlin. Before coming to Sweden, she was Assistant Professor at the University of Hamburg in Germany. She received her Ph.D. in Mathematics at the Academy of Sciences of the GDR. Since 1991, she has taught Statistics for undergraduate and graduate students. Her research interests have moved from theoretical statistics to computer intensive statistics. Behrang Mahjani is a postdoctoral fellow with a Ph.D. in Scientific Computing with a focus on Computational Statistics, from Uppsala University, Sweden. He joined the Seaver Autism Center for Research and Treatment at the Icahn School of Medicine at Mount Sinai, New York, in September 2017 and was formerly a postdoctoral fellow at the Karolinska Institutet, Stockholm, Sweden. His research is focused on solving large-scale problems through statistical and computational methods.

Author : Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Publisher : Springer
Page : 0 pages
File Size : 54,9 Mb
Release : 2018-07-05
Category : Mathematics
ISBN : 9811096627

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Advanced Statistical Methods in Data Science by Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu Pdf

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Author : Rudolf Dutter
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 46,6 Mb
Release : 2003
Category : Business & Economics
ISBN : 3790815187

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Developments in Robust Statistics by Rudolf Dutter Pdf

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

Author : Jana Jureckova,Jan Picek
Publisher : CRC Press
Page : 210 pages
File Size : 47,6 Mb
Release : 2005-11-29
Category : Mathematics
ISBN : 9781420035131

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Robust Statistical Methods with R by Jana Jureckova,Jan Picek Pdf

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systemati

Author : Ricardo A. Maronna,R. Douglas Martin,Victor J. Yohai,Matías Salibián-Barrera
Publisher : John Wiley & Sons
Page : 466 pages
File Size : 50,6 Mb
Release : 2019-01-04
Category : Mathematics
ISBN : 9781119214687

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Robust Statistics by Ricardo A. Maronna,R. Douglas Martin,Victor J. Yohai,Matías Salibián-Barrera Pdf

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.

Author : Rudolf Dutter,Peter Filzmoser,Ursula Gather,Peter J. Rousseeuw
Publisher : Springer Science & Business Media
Page : 445 pages
File Size : 55,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642573385

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Developments in Robust Statistics by Rudolf Dutter,Peter Filzmoser,Ursula Gather,Peter J. Rousseeuw Pdf

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

Author : Georgy L. Shevlyakov,Nikita O. Vilchevski
Publisher : Walter de Gruyter
Page : 325 pages
File Size : 48,8 Mb
Release : 2011-12-07
Category : Mathematics
ISBN : 9783110936001

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Robustness in Data Analysis by Georgy L. Shevlyakov,Nikita O. Vilchevski Pdf

The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.

Author : Anonim
Publisher : Maggioli Editore
Page : 493 pages
File Size : 43,6 Mb
Release : 2009
Category : Business & Economics
ISBN : 9788838743856

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S. Co. 2009. Sixth Conference. Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction by Anonim Pdf

Author : Stephane Heritier,Eva Cantoni,Samuel Copt,Maria-Pia Victoria-Feser
Publisher : John Wiley & Sons
Page : 292 pages
File Size : 40,5 Mb
Release : 2009-05-11
Category : Medical
ISBN : 047074054X

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Robust Methods in Biostatistics by Stephane Heritier,Eva Cantoni,Samuel Copt,Maria-Pia Victoria-Feser Pdf

Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.

Author : Mengxi Yi,Klaus Nordhausen
Publisher : Springer Nature
Page : 500 pages
File Size : 43,5 Mb
Release : 2023-04-19
Category : Mathematics
ISBN : 9783031226878

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Robust and Multivariate Statistical Methods by Mengxi Yi,Klaus Nordhausen Pdf

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.

Author : Robert Andersen
Publisher : SAGE
Page : 129 pages
File Size : 43,9 Mb
Release : 2008
Category : Mathematics
ISBN : 9781412940726

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Modern Methods for Robust Regression by Robert Andersen Pdf

Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.

Author : Rand R. Wilcox
Publisher : Academic Press
Page : 810 pages
File Size : 49,6 Mb
Release : 2016-09-02
Category : Mathematics
ISBN : 9780128047811

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Introduction to Robust Estimation and Hypothesis Testing by Rand R. Wilcox Pdf

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a ‘how-to’ on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions. New to this edition 35% revised content Covers many new and improved R functions New techniques that deal with a wide range of situations Extensive revisions to cover the latest developments in robust regression Covers latest improvements in ANOVA Includes newest rank-based methods Describes and illustrated easy to use software

Author : W.N. Venables,B.D. Ripley
Publisher : Springer Science & Business Media
Page : 501 pages
File Size : 51,7 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9780387217062

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Modern Applied Statistics with S by W.N. Venables,B.D. Ripley Pdf

A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.