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Modern Nonparametric, Robust and Multivariate Methods

Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and;

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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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Multivariate Nonparametric Regression And Visualization

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation;

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Robust Nonparametric Statistical Methods

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers;

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Multivariate Density Estimation

Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods;

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Regression And Time Series Model Selection

selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including;

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Robust Multivariate Analysis

theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed;

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Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications

yet rigorous presentation of advanced nonparametric and robust methods, with applications for the analysis of economies of scale and scope;

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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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Multivariate Permutation Tests

results. Permutation and nonparametric combination methods provide flexible solutions to complex problems by reducing the problem down to a set;

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Growth Curves

experiments, covering time-moving covariates, exchangable errors, bioassay results, missing data procedures and nonparametric and Bayesian methods.;

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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

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

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Contributions to Static and Time-Varying Copula-Based Modeling of Multivariate Association

Putting a particular emphasis on nonparametric methods that rely on modern empirical process techniques, the author contributes to the;

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Robust Correlation Theory & Aplications

: * Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working;

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Nonparametric Statistical Methods Using R

. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for;

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Nonparametric Statistical Methods Using R

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers;

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Exploring Data Tables, Trends, And Shapes

Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data;

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Nonparametric Econometric Methods

Methods', and the papers selected for inclusion in this Volume span a range of nonparametric techniques including kernel smoothing, empirical;

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Nonparametric Finance

An Introduction to Machine Learning in Finance, With Mathematical Background, Data Visualization, and R Nonparametric function;

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All of Nonparametric Statistics

want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta;

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Observed Confidence Levels

in statistical inference. It focuses on the modern nonparametric framework of bootstrap-based estimates, allowing for substantial theoretical development;

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Observed Confidence Levels

in statistical inference. It focuses on the modern nonparametric framework of bootstrap-based estimates, allowing for substantial theoretical development;

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Nonparametric Statistical Methods

Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical;

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Ranking of Multivariate Populations

analysis by image processing. A web-based nonparametric combination global ranking software is also described. Designed for practitioners and;

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Frontiers In Statistics

have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric;

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