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Author : Prabir Burman
Publisher :
ISBN 13 :
Total Pages : 66 pages
Book Rating : 4.:/5 (844 download)
Download or read book Smoothing in discrete multivariate analysis written by Prabir Burman and published by . This book was released on 1985 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yvonne M. Bishop
Publisher : Springer Science & Business Media
ISBN 13 : 0387728058
Total Pages : 558 pages
Book Rating : 4.3/5 (877 download)
Download or read book Discrete Multivariate Analysis written by Yvonne M. Bishop and published by Springer Science & Business Media. This book was released on 2007-07-30 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: “A welcome addition to multivariate analysis. The discussion is lucid and very leisurely, excellently illustrated with applications drawn from a wide variety of fields. A good part of the book can be understood without very specialized statistical knowledge. It is a most welcome contribution to an interesting and lively subject.” -- Nature Originally published in 1974, this book is a reprint of a classic, still-valuable text.
Author : Jussi Sakari Klemelä
Publisher : John Wiley & Sons
ISBN 13 : 0470425660
Total Pages : 641 pages
Book Rating : 4.4/5 (74 download)
Download or read book Smoothing of Multivariate Data written by Jussi Sakari Klemelä and published by John Wiley & Sons. This book was released on 2009-09-04 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data Smoothing of Multivariate Data provides an illustrative and hands-on approach to the multivariate aspects of density estimation, emphasizing the use of visualization tools. Rather than outlining the theoretical concepts of classification and regression, this book focuses on the procedures for estimating a multivariate distribution via smoothing. The author first provides an introduction to various visualization tools that can be used to construct representations of multivariate functions, sets, data, and scales of multivariate density estimates. Next, readers are presented with an extensive review of the basic mathematical tools that are needed to asymptotically analyze the behavior of multivariate density estimators, with coverage of density classes, lower bounds, empirical processes, and manipulation of density estimates. The book concludes with an extensive toolbox of multivariate density estimators, including anisotropic kernel estimators, minimization estimators, multivariate adaptive histograms, and wavelet estimators. A completely interactive experience is encouraged, as all examples and figurescan be easily replicated using the R software package, and every chapter concludes with numerous exercises that allow readers to test their understanding of the presented techniques. The R software is freely available on the book's related Web site along with "Code" sections for each chapter that provide short instructions for working in the R environment. Combining mathematical analysis with practical implementations, Smoothing of Multivariate Data is an excellent book for courses in multivariate analysis, data analysis, and nonparametric statistics at the upper-undergraduate and graduatelevels. It also serves as a valuable reference for practitioners and researchers in the fields of statistics, computer science, economics, and engineering.
Author : Yvonne M. M. Bishop
Publisher :
ISBN 13 :
Total Pages : 557 pages
Book Rating : 4.:/5 (243 download)
Download or read book Discrete multivariate analysis written by Yvonne M. M. Bishop and published by . This book was released on 1980 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jeffrey S. Simonoff
Publisher : Springer Science & Business Media
ISBN 13 : 1461240263
Total Pages : 349 pages
Book Rating : 4.4/5 (612 download)
Download or read book Smoothing Methods in Statistics written by Jeffrey S. Simonoff and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be of particular interest to data analysts, as arguments generally proceed from actual data rather than statistical theory, while the "Background Material" sections will interest statisticians studying the field. Over 750 references allow researchers to find the original sources for more details, and the "Computational Issues" sections provide sources for statistical software that use the methods discussed. Each chapter includes exercises with a heavily computational focus based upon the data sets used in the book, making it equally suitable as a textbook for a course in smoothing.
Author : Thomas J. Santner
Publisher : Springer Science & Business Media
ISBN 13 : 1461210178
Total Pages : 381 pages
Book Rating : 4.4/5 (612 download)
Download or read book The Statistical Analysis of Discrete Data written by Thomas J. Santner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Statistical Analysis of Discrete Data provides an introduction to cur rent statistical methods for analyzing discrete response data. The book can be used as a course text for graduate students and as a reference for researchers who analyze discrete data. The book's mathematical prereq uisites are linear algebra and elementary advanced calculus. It assumes a basic statistics course which includes some decision theory, and knowledge of classical linear model theory for continuous response data. Problems are provided at the end of each chapter to give the reader an opportunity to ap ply the methods in the text, to explore extensions of the material covered, and to analyze data with discrete responses. In the text examples, and in the problems, we have sought to include interesting data sets from a wide variety of fields including political science, medicine, nuclear engineering, sociology, ecology, cancer research, library science, and biology. Although there are several texts available on discrete data analysis, we felt there was a need for a book which incorporated some of the myriad recent research advances. Our motivation was to introduce the subject by emphasizing its ties to the well-known theories of linear models, experi mental design, and regression diagnostics, as well as to describe alterna tive methodologies (Bayesian, smoothing, etc. ); the latter are based on the premise that external information is available. These overriding goals, to gether with our own experiences and biases, have governed our choice of topics.
Author : Yvonne Millicent Mahala Bishop
Publisher : MIT Press (MA)
ISBN 13 :
Total Pages : 576 pages
Book Rating : 4.:/5 ( download)
Download or read book Discrete Multivariate Analysis: Theory and Practice written by Yvonne Millicent Mahala Bishop and published by MIT Press (MA). This book was released on 1975 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural models for counted data; Maximum likelihood estimates for complete tables; Formal goodness of fit: summary statistics and model selection; Maximum likelihood estimation for incomplete tables; Estimating the size of a closed population; Models for measuring change; Analysis of square tables: symmetry and marginal homogeneity; Model selection and assessing closeness of fit: practical aspects; Other methods for estimation and testing in cross-classifications; Measures of association and agreement; Pseudo-bayes estimates of cell probabilities; Sampling models for discrete data; Asymptotic methods.
Author : Timothy R.C. Read
Publisher : Springer Science & Business Media
ISBN 13 : 1461245788
Total Pages : 221 pages
Book Rating : 4.4/5 (612 download)
Download or read book Goodness-of-Fit Statistics for Discrete Multivariate Data written by Timothy R.C. Read and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistical analysis of discrete multivariate data has received a great deal of attention in the statistics literature over the past two decades. The develop ment ofappropriate models is the common theme of books such as Cox (1970), Haberman (1974, 1978, 1979), Bishop et al. (1975), Gokhale and Kullback (1978), Upton (1978), Fienberg (1980), Plackett (1981), Agresti (1984), Goodman (1984), and Freeman (1987). The objective of our book differs from those listed above. Rather than concentrating on model building, our intention is to describe and assess the goodness-of-fit statistics used in the model verification part of the inference process. Those books that emphasize model development tend to assume that the model can be tested with one of the traditional goodness-of-fit tests 2 2 (e.g., Pearson's X or the loglikelihood ratio G ) using a chi-squared critical value. However, it is well known that this can give a poor approximation in many circumstances. This book provides the reader with a unified analysis of the traditional goodness-of-fit tests, describing their behavior and relative merits as well as introducing some new test statistics. The power-divergence family of statistics (Cressie and Read, 1984) is used to link the traditional test statistics through a single real-valued parameter, and provides a way to consolidate and extend the current fragmented literature. As a by-product of our analysis, a new 2 2 statistic emerges "between" Pearson's X and the loglikelihood ratio G that has some valuable properties.
Author : R. J. Flowers
Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (173 download)
Download or read book Discrete Multivariate Analysis Using Log-linear Models written by R. J. Flowers and published by . This book was released on 1981 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David W. Scott
Publisher : John Wiley & Sons
ISBN 13 : 1118575539
Total Pages : 384 pages
Book Rating : 4.1/5 (185 download)
Download or read book Multivariate Density Estimation written by David W. Scott and published by John Wiley & Sons. This book was released on 2015-03-12 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.
Author : José E. Chacón
Publisher : CRC Press
ISBN 13 : 0429939140
Total Pages : 226 pages
Book Rating : 4.4/5 (299 download)
Download or read book Multivariate Kernel Smoothing and Its Applications written by José E. Chacón and published by CRC Press. This book was released on 2018-05-08 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kernel smoothing has greatly evolved since its inception to become an essential methodology in the data science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite solutions to complex data challenges. Multivariate Kernel Smoothing and Its Applications offers a comprehensive overview of both aspects. It begins with a thorough exposition of the approaches to achieve the two basic goals of estimating probability density functions and their derivatives. The focus then turns to the applications of these approaches to more complex data analysis goals, many with a geometric/topological flavour, such as level set estimation, clustering (unsupervised learning), principal curves, and feature significance. Other topics, while not direct applications of density (derivative) estimation but sharing many commonalities with the previous settings, include classification (supervised learning), nearest neighbour estimation, and deconvolution for data observed with error. For a data scientist, each chapter contains illustrative Open data examples that are analysed by the most appropriate kernel smoothing method. The emphasis is always placed on an intuitive understanding of the data provided by the accompanying statistical visualisations. For a reader wishing to investigate further the details of their underlying statistical reasoning, a graduated exposition to a unified theoretical framework is provided. The algorithms for efficient software implementation are also discussed. José E. Chacón is an associate professor at the Department of Mathematics of the Universidad de Extremadura in Spain. Tarn Duong is a Senior Data Scientist for a start-up which provides short distance carpooling services in France. Both authors have made important contributions to kernel smoothing research over the last couple of decades.
Author : Kenneth Train
Publisher : Cambridge University Press
ISBN 13 : 0521766559
Total Pages : 399 pages
Book Rating : 4.5/5 (217 download)
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author : M.P. Wand
Publisher : CRC Press
ISBN 13 : 9780412552700
Total Pages : 230 pages
Book Rating : 4.5/5 (527 download)
Download or read book Kernel Smoothing written by M.P. Wand and published by CRC Press. This book was released on 1994-12-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function. This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilitated by the authors' focus on the simplest settings, namely density estimation and nonparametric regression. They pay particular attention to the problem of choosing the smoothing parameter of a kernel smoother, and also treat the multivariate case in detail. Kernal Smoothing is self-contained and assumes only a basic knowledge of statistics, calculus, and matrix algebra. It is an invaluable introduction to the main ideas of kernel estimation for students and researchers from other discipline and provides a comprehensive reference for those familiar with the topic.
Author : Michael G. Schimek
Publisher : John Wiley & Sons
ISBN 13 : 1118763300
Total Pages : 682 pages
Book Rating : 4.1/5 (187 download)
Download or read book Smoothing and Regression written by Michael G. Schimek and published by John Wiley & Sons. This book was released on 2013-05-29 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis. Using examples of applications from the biosciences, environmental sciences, engineering, and economics, as well as medical research and marketing, this volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special features of this book include: * Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines * A unified, easy-to-follow format * Contributions from more than 25 leading researchers from around the world * More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems * Extensive end-of-chapter references For professionals and aspiring professionals in statistics, applied mathematics, computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.
Author : Sadanori Konishi
Publisher : CRC Press
ISBN 13 : 1466567295
Total Pages : 338 pages
Book Rating : 4.4/5 (665 download)
Download or read book Introduction to Multivariate Analysis written by Sadanori Konishi and published by CRC Press. This book was released on 2014-06-06 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Select the Optimal Model for Interpreting Multivariate DataIntroduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedu
Author : Daniel Zelterman
Publisher : Oxford University Press
ISBN 13 : 9780198524366
Total Pages : 233 pages
Book Rating : 4.5/5 (243 download)
Download or read book Models for Discrete Data written by Daniel Zelterman and published by Oxford University Press. This book was released on 1999 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete or count data arise in experiments where the outcome variables are the numbers of individuals classified into unique, non-overlapping categories. This book describes the statistical models used in the analysis and summary of such data, and provides an introduction to the subject for graduate students and practitioners needing a review of the methodology. It includes topics not covered in depth elsewhere, such as the negative multinomial distribution; the many forms of the hypergeometric distribution; and coordinate free models.
Author : W. J. Krzanowski
Publisher : Oxford University Press
ISBN 13 : 0198507089
Total Pages : 609 pages
Book Rating : 4.1/5 (985 download)
Download or read book Principles of Multivariate Analysis written by W. J. Krzanowski and published by Oxford University Press. This book was released on 2000-09-28 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis is necessary whenever more than one characteristic is observed on each individual under study. Applications arise in very many areas of study. This book provides a comprehensive introduction to available techniques for analysing date of this form, written in a style that should appeal to non-specialists as well as to statisticians. In particular, geometric intuition is emphasized in preference to algebraic manipulation wherever possible. The new edition includes a survey of the most recent developments in the subject.
