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Introduction to Robust and Quasi-Robust Statistical Methods

Introduction to Robust and Quasi-Robust Statistical Methods is een boek van William J.J. Rey;

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Robust Statistics

Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into;

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Robust Estimation And Testing

Offering an introduction to the theory and methods of robust statistics at an intermediate level, this work aims to illustrate the need for;

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Modern Nonparametric, Robust and Multivariate Methods

multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust;

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Theory And Applications Of Recent Robust Methods

Intended for both researchers and practitioners, this book will be a valuable resource for studying and applying recent robust statistical;

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Methodology in Robust and Nonparametric Statistics

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from;

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Methodology in Robust and Nonparametric Statistics

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from;

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Robust Statistics

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation;

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Robust Statistical Methods with R, Second Edition

researchers and postgraduate students in statistics and mathematics. Features * Provides a systematic, practical treatment of robust statistical;

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Robust Statistical Methods with R, Second Edition

The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new;

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Robust Nonlinear Regression

is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust;

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Understanding Robust And Exploratory Data Analysis

some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use;

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Robust Design For Quality Engineering And Six Sigma

This book is written primarily for engineers and researchers who use statistical robust design for quality engineering and Six Sigma, and;

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Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful 'how-to' on the application of robust methods utilizing;

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Simulation and Robust Statistics

This book addresses the topics statistical simulation and robust estimation. It is accompanied by several software packages for the open;

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Robust Multivariate Analysis

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain;

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Introduction to Robust Estimation and Hypothesis Testing

in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications;

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Robust Methods in Biostatistics

to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not;

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Recent Advances in Robust Statistics: Theory and Applications

is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports;

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Robust Statistics

, Robust Statistics , Second Edition continues to provide an authoritative and systematic treatment of the topic. This new edition has been;

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Introduction to Multivariate Statistical Analysis in Chemometrics

Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical;

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The Robust Multigrid Technique

close-to-optimal algorithmic complexity and the least number of problem-dependent components. Topics covered include an introduction to the;

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Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon,is a 'how-to' on the application of robust methods using available;

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Regression And Time Series Model Selection

wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are;

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Understanding and Applying Basic Statistical Methods Using R

), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for;

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Statistical Process Monitoring and Optimization

Demonstrates ways to track industrial processes and performance, integrating related areas such as engineering process control, statistical;

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Statistical Robust Design

A UNIQUELY PRACTICAL APPROACH TO ROBUST DESIGN FROM A STATISTICAL AND ENGINEERING PERSPECTIVE Variation in environment, usage conditions;

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