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Density Estimation for Statistics and Data Analysis

. This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data;

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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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Nonparametric Function Estimation, Modeling, and Simulation

, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation;

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Nonparametric Methods in Statistics with SAS Applications

analysis, density estimation, and resampling methods. The text begins with classical nonparametric hypotheses testing, including the sign;

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Nonparametric Methods In Statistics With Sas Applications

analysis, density estimation, and resampling methods. The text begins with classical nonparametric hypotheses testing, including the sign;

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Mathematical Statistics

density estimation. For students with some elementary mathematical background. With many exercises. Updated, completeSolutions Manual;

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Functional and High-Dimensional Statistics and Related Fields

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Statistical Inference

developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models;

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Statistical Inference

in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also;

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Smoothing of Multivariate Data

of Multivariate Data provides an illustrative and hands-on approach to the multivariate aspects of density estimation, emphasizing the use;

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Statistical Modeling Using Local Gaussian Approximation

explores Measuring dependence and testing for independence, Time series dependence and spectral analysis, Multivariate density estimation;

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Elements of Statistical Computing

point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive;

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Smoothing Methods in Statistics

Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation;

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Graphics for Statistics and Data Analysis with R

of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies;

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Graphics for Statistics and Data Analysis with R

analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion;

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An Introduction to Nonparametric Statistics

Density estimation is explored The bootstrap and jackknife are discussed This text is intended for a graduate student in applied;

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Probability and Statistics

basics of sampling distributions, estimation and hypothesis testing. As a companion for classes for engineers and scientists, the book also;

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Modern Directional Statistics

, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley;

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Modern Directional Statistics

, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor;

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Quantitative Genetics And Its Connections With Big Data And Sequenced Genomes

relatively small sets of data. In this book, new methods of direct estimation are introduced and analyzed that are appropriate for an era of big sets;

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Quantitative Genetics And Its Connections With Big Data And Sequenced Genomes

relatively small sets of data. In this book, new methods of direct estimation are introduced and analyzed that are appropriate for an era of big sets;

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Introductory Statistics

An updated and revised edition of the popular introduction to statistics for students of economics or business, suitable for a one-- or two;

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High-Dimensional Covariance Estimation

graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.;

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Kernel Smoothing

, applications, and analysis of kernel smoothers. This is facilitated by the authors' focus on the simplest settings, namely density estimation and;

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Statistics and Analysis of Scientific Data

Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and;

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