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Author : Peter Verboon
Publisher :
ISBN 13 : 9789090070094
Total Pages : 189 pages
Book Rating : 4.0/5 (7 download)
Download or read book A Robust Approach to Nonlinear Multivariate Analysis written by Peter Verboon and published by . This book was released on 1994 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter Verboon
Publisher :
ISBN 13 :
Total Pages : 214 pages
Book Rating : 4.3/5 (91 download)
Download or read book A Robust Approach to Nonlinear Multivariate Analysis written by Peter Verboon and published by . This book was released on 1994 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jacqueline Meulman
Publisher :
ISBN 13 :
Total Pages : 222 pages
Book Rating : 4.3/5 (91 download)
Download or read book A Distance Approach to Nonlinear Multivariate Analysis written by Jacqueline Meulman and published by . This book was released on 1986 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis and multidimensional scaling. Classification of MVA techniques: join and meet. STRIFE. STRAIN. STRESS. The majorization algorithm-model. Notation. Multivariate analysis via strife. The gifi system of nonlinear multivariate analysis. Join and meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis via join-STRIFE. Nonlinear principal components analysis via Meet-STRIFE. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Normalization. Multivariate analysis via strain. Distance properties of multivariate analysis. Join and meet. Principal components analysis. Canonical coordinates analysis. Homogeneity analysis. The asymmetric treatment of rows and columns. From classical to nonlinear multivariate analysis. Multivariate analysis via stress. From STRAIN to STRESS via multidimensional scaling. Multidimensional scaling with restrictions. Join and Meet. Homogeneity analysis. Principal components analysis. Classical principal components analysis. Nonlinear principal components analysis. Canonical coordinates analysis. Classical canonical coordinates analysis. Nonlinear canonical coordinates analysis. Cone regression with a non-diagonal weight matrix. Summary of the algorithm for nonlinear canonical coordinates analysis. Some special techniques in the stress framework. Simultaneous nonlinear principal components analysis with M sets. Asymmetric treatment of sets. Nonlinear redundancy analysis. Distance driven subspace approximation. Composite nonlinear principal components analysis. The majorization algorithm for multidimensional scaling. Overview of applications. Applications of multivariate analysis via strife. Homogeneity analysis of cetacea. Nonlinear principal components analysis of the United States. Nonlinear canonical coordinates analysis of the United States. Applications of multivariate analysis via strain. Principal coordinates analysis of city crime. Principal components analysis of city crime. Canonical coordinates analysis of the Southern States. Correspondence analysis and principal coordinates analysis of the parliament. Principal components analysis and classical MDS of criminal correlations. Applications of multivariate analysis via stress. Principal coordinates analysis of the parliament. Principal coordinates analysis of the parliament via constrained MDS. Homogeneity analysis of cetacea. Classical principal components analysis of city crime. Nonlinear principal components analysis of the United States. Classical canonical coordinates analysis of the Southern State. Nonlinear canonical coordinates analysis of the United States. Nonlinear redundancy analysis of the United States. Composite nonlinear principal components analysis of the United States.
Author :
Publisher :
ISBN 13 : 9788126545117
Total Pages : 579 pages
Book Rating : 4.5/5 (451 download)
Download or read book Nonlinear Multivariate Analysis written by and published by . This book was released on 1990 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jacqueline Jacinthe Meulman
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 (489 download)
Download or read book A Distance Approach to Nonlinear Multivariate Analysis written by Jacqueline Jacinthe Meulman and published by . This book was released on 1986 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Albert Gifi
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 608 pages
Book Rating : 4.:/5 (44 download)
Download or read book Nonlinear Multivariate Analysis written by Albert Gifi and published by John Wiley & Sons. This book was released on 1990 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conventions and controversies in multivariate analysis; Coding of categorical data; Homogeneity analysis; Nonlinear principal components analysis; Nonlinear generalized canonical analysis; Nonlinear canonical correlation analysis; Asymmetric treatment of sets: some special cases, some future programs; Multidimensional scaling and correspondende analysis; Models as gauges for the analysis of binary data; Reflections on restrictions; Nonlinear multivariate analysis: principles and possibilities; The study of stability; The proof of the pudding.
Author : Hossein Riazoshams
Publisher : John Wiley & Sons
ISBN 13 : 1119010454
Total Pages : 264 pages
Book Rating : 4.1/5 (19 download)
Download or read book Robust Nonlinear Regression written by Hossein Riazoshams and published by John Wiley & Sons. This book was released on 2018-06-11 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to discuss robust aspects of nonlinear regression—with applications using R software Robust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust aspects of nonlinear regression and focuses on outlier effects. It develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language under SPLUS and R software. The software covers a wide range of robust nonlinear fitting and inferences, and is designed to provide facilities for computer users to define their own nonlinear models as an object, and fit models using classic and robust methods as well as detect outliers. The implemented objects and functions can be applied by practitioners as well as researchers. The book offers comprehensive coverage of the subject in 9 chapters: Theories of Nonlinear Regression and Inference; Introduction to R; Optimization; Theories of Robust Nonlinear Methods; Robust and Classical Nonlinear Regression with Autocorrelated and Heteroscedastic errors; Outlier Detection; R Packages in Nonlinear Regression; A New R Package in Robust Nonlinear Regression; and Object Sets. The first comprehensive coverage of this field covers a variety of both theoretical and applied topics surrounding robust nonlinear regression Addresses some commonly mishandled aspects of modeling R packages for both classical and robust nonlinear regression are presented in detail in the book and on an accompanying website Robust Nonlinear Regression: with Applications using R is an ideal text for statisticians, biostatisticians, and statistical consultants, as well as advanced level students of statistics.
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 : Shizuhiko Nishisato
Publisher : CRC Press
ISBN 13 : 9781584886129
Total Pages : 336 pages
Book Rating : 4.8/5 (861 download)
Download or read book Multidimensional Nonlinear Descriptive Analysis written by Shizuhiko Nishisato and published by CRC Press. This book was released on 2006-06-26 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations. This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for future progress. Covering both the early and later years of MUNDA research in the social sciences, psychology, ecology, biology, and statistics, this book provides a framework for potential developments in even more areas of study.
Author : Shizuhiko Nishisato
Publisher : Springer Nature
ISBN 13 : 9811624704
Total Pages : 231 pages
Book Rating : 4.8/5 (116 download)
Download or read book Modern Quantification Theory written by Shizuhiko Nishisato and published by Springer Nature. This book was released on 2021-07-22 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis. These multiple identities are a consequence of its large number of properties that allow one to analyze and visualize the strength of variable association in an optimal solution. The book contains modern quantification theory for analyzing the association between two and more categorical variables in a variety of applicative frameworks. Visualization has attracted much attention over the past decades and given rise to controversial opinions. One may consider variations of plotting systems used in the construction of the classic correspondence plot, the biplot, the Carroll-Green-Schaffer scaling, or a new approach in doubled multidimensional space as presented in the book. There are even arguments for no visualization at all. The purpose of this book therefore is to shed new light on time-honored graphical procedures with critical reviews, new ideas, and future directions as alternatives. This stimulating volume is written with fresh new ideas from the traditional framework and the contemporary points of view. It thus offers readers a deep understanding of the ever-evolving nature of quantification theory and its practice. Part I starts with illustrating contingency table analysis with traditional joint graphical displays (symmetric, non-symmetric) and the CGS scaling and then explores logically correct graphs in doubled Euclidean space for both row and column variables. Part II covers a variety of mathematical approaches to the biplot strategy in graphing a data structure, providing a useful source for this modern approach to graphical display. Part II is also concerned with a number of alternative approaches to the joint graphical display such as bimodal cluster analysis and other statistical problems relevant to quantification theory.
Author : David J. Olive
Publisher : Springer
ISBN 13 : 3319682539
Total Pages : 508 pages
Book Rating : 4.3/5 (196 download)
Download or read book Robust Multivariate Analysis written by David J. Olive and published by Springer. This book was released on 2017-11-28 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.
Author : Maurizio Vichi
Publisher : Springer Science & Business Media
ISBN 13 : 3540273735
Total Pages : 372 pages
Book Rating : 4.5/5 (42 download)
Download or read book New Developments in Classification and Data Analysis written by Maurizio Vichi and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains revised versions of selected papers presented during the biannual meeting of the Classification and Data Analysis Group of SocietA Italiana di Statistica, which was held in Bologna, September 22-24, 2003. The scientific program of the conference included 80 contributed papers. Moreover it was possible to recruit six internationally renowned invited spe- ers for plenary talks on their current research works regarding the core topics of IFCS (the International Federation of Classification Societies) and Wo- gang Gaul and the colleagues of the GfKl organized a session. Thus, the conference provided a large number of scientists and experts from home and abroad with an attractive forum for discussions and mutual exchange of knowledge. The talks in the different sessions focused on methodological developments in supervised and unsupervised classification and in data analysis, also p- viding relevant contributions in the context of applications. This suggested the presentation of the 43 selected papers in three parts as follows: CLASSIFICATION AND CLUSTERING Non parametric classification Clustering and dissimilarities MULTIVARIATE STATISTICS AND DATA ANALYSIS APPLIED MULTIVARIATE STATISTICS Environmental data Microarray data Behavioural and text data Financial data We wish to express our gratitude to the authors whose enthusiastic p- ticipation made the meeting possible. We are very grateful to the reviewers for the time spent in their professional reviewing work. We would also like to extend our thanks to the chairpersons and discussants of the sessions: their comments and suggestions proved very stimulating both for the authors and the audience.
Author : Shizuhiko Nishisato
Publisher : Springer Nature
ISBN 13 : 981992295X
Total Pages : 214 pages
Book Rating : 4.8/5 (199 download)
Download or read book Measurement, Mathematics and New Quantification Theory written by Shizuhiko Nishisato and published by Springer Nature. This book was released on 2023-06-12 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to thoroughly prepare diverse areas of researchers in quantification theory. As is well known, quantification theory has attracted the attention of a countless number of researchers, some mathematically oriented and others not, but all of them are experts in their own disciplines. Quantifying non-quantitative (qualitative) data requires a variety of mathematical and statistical strategies, some of which are quite complicated. Unlike many books on quantification theory, the current book places more emphasis on preliminary requisites of mathematical tools than on details of quantification theory. As such, the book is primarily intended for readers whose specialty is outside mathematical sciences. The book was designed to offer non-mathematicians a variety of mathematical tools used in quantification theory in simple terms. Once all the preliminaries are fully discussed, quantification theory is then introduced in the last section as a simple application of those mathematical procedures fully discussed so far. The book opens up further frontiers of quantification theory as simple applications of basic mathematics.
Author : Nickolay Trendafilov
Publisher : Springer Nature
ISBN 13 : 3030769747
Total Pages : 467 pages
Book Rating : 4.0/5 (37 download)
Download or read book Multivariate Data Analysis on Matrix Manifolds written by Nickolay Trendafilov and published by Springer Nature. This book was released on 2021-09-15 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.
Author : Yoshio Takane
Publisher : CRC Press
ISBN 13 : 1466556684
Total Pages : 244 pages
Book Rating : 4.4/5 (665 download)
Download or read book Constrained Principal Component Analysis and Related Techniques written by Yoshio Takane and published by CRC Press. This book was released on 2016-04-19 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? Wha
Author : Ingwer Borg
Publisher : Springer Science & Business Media
ISBN 13 : 1475727119
Total Pages : 469 pages
Book Rating : 4.4/5 (757 download)
Download or read book Modern Multidimensional Scaling written by Ingwer Borg and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.
Author : R Murray-Smith
Publisher : CRC Press
ISBN 13 : 1000162761
Total Pages : 360 pages
Book Rating : 4.0/5 (1 download)
Download or read book Multiple Model Approaches To Nonlinear Modelling And Control written by R Murray-Smith and published by CRC Press. This book was released on 2020-11-26 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents approaches to modelling and control problems arising from conditions of ever increasing nonlinearity and complexity. It prescribes an approach that covers a wide range of methods being combined to provide multiple model solutions. Many component methods are described, as well as discussion of the strategies available for building a successful multiple model approach.
