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Author: Peter .J. Bickel Publisher: CRC Press ISBN: 9780534980443 Category : Mathematics Languages : en Pages : 478
Book Description
A collection of essays and articles In honour of Erich. L. Lehmann's sixty-fifth birthday. Including works on Vector Autoregressive models, Bootstrapping Regression Models, Bootstrapping Regression Models and Estimation of the Mean or Total when Measurement Protocols.
Author: Peter .J. Bickel Publisher: CRC Press ISBN: 9780534980443 Category : Mathematics Languages : en Pages : 478
Book Description
A collection of essays and articles In honour of Erich. L. Lehmann's sixty-fifth birthday. Including works on Vector Autoregressive models, Bootstrapping Regression Models, Bootstrapping Regression Models and Estimation of the Mean or Total when Measurement Protocols.
Author: Javier Rojo Publisher: Springer Science & Business Media ISBN: 1461414113 Category : Mathematics Languages : en Pages : 1103
Book Description
These volumes present a selection of Erich L. Lehmann’s monumental contributions to Statistics. These works are multifaceted. His early work included fundamental contributions to hypothesis testing, theory of point estimation, and more generally to decision theory. His work in Nonparametric Statistics was groundbreaking. His fundamental contributions in this area include results that came to assuage the anxiety of statisticians that were skeptical of nonparametric methodologies, and his work on concepts of dependence has created a large literature. The two volumes are divided into chapters of related works. Invited contributors have critiqued the papers in each chapter, and the reprinted group of papers follows each commentary. A complete bibliography that contains links to recorded talks by Erich Lehmann – and which are freely accessible to the public – and a list of Ph.D. students are also included. These volumes belong in every statistician’s personal collection and are a required holding for any institutional library.
Author: Erich L. Lehmann Publisher: Springer Science & Business Media ISBN: 0387715975 Category : Mathematics Languages : en Pages : 319
Book Description
This relatively nontechnical book is the first account of the history of statistics from the Fisher revolution to the computer revolution. It sketches the careers, and highlights some of the work, of 65 people, most of them statisticians. What gives the book its special character is its emphasis on the author's interaction with these people and the inclusion of many personal anecdotes. Combined, these portraits provide an amazing fly-on-the-wall view of statistics during the period in question. The stress is on ideas and technical material is held to a minimum. Thus the book is accessible to anyone with at least an elementary background in statistics.
Author: Georgy L. Shevlyakov Publisher: John Wiley & Sons ISBN: 1119264537 Category : Mathematics Languages : en Pages : 352
Book Description
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.
Author: Bradley Efron Publisher: CRC Press ISBN: 9780412042317 Category : Mathematics Languages : en Pages : 456
Book Description
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
Author: David C. Hoaglin Publisher: John Wiley & Sons ISBN: 1118150694 Category : Mathematics Languages : en Pages : 564
Book Description
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area." —Technometrics "This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously." —The Statistician This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.
Author: Hannu Oja Publisher: Springer Science & Business Media ISBN: 1441904689 Category : Mathematics Languages : en Pages : 239
Book Description
This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory. Hannu Oja is an academy professor and a professor in biometry in the University of Tampere. He has authored and coauthored numerous research articles in multivariate nonparametrical and robust methods as well as in biostatistics.
Author: Regina Y. Liu Publisher: American Mathematical Soc. ISBN: 0821835963 Category : Mathematics Languages : en Pages : 264
Book Description
The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University. The workshop brought together researchers from two different communities: statisticians and specialists in computational geometry. The main idea unifying these two research areas turned out to be the notion of data depth, which is an important notion both in statistics and in the study of efficiency of algorithms used in computational geometry. Many of the articles in the book lay down the foundations for further collaboration and interdisciplinary research. Information for our distributors: Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with the Association for Computer Machinery (ACM).
Author: Peter .J. Bickel
Author: Peter .J. Bickel
Author: Erich Leo Lehmann
Author: 
Author: Javier Rojo
Author: Erich L. Lehmann
Author: Georgy L. Shevlyakov
Author: Bradley Efron
Author: David C. Hoaglin
Author: Hannu Oja
Author: Regina Y. Liu