Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Large Variable Canonical Analysis full books in PDF, epub, and Kindle. Read online Large Variable Canonical Analysis ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Sharon Lawner Weinberg
Publisher :
ISBN 13 :
Total Pages : 244 pages
Book Rating : 4.E/5 ( download)
Download or read book Large Variable Canonical Analysis written by Sharon Lawner Weinberg and published by . This book was released on 1971 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Brian Everitt
Publisher : Springer Science & Business Media
ISBN 13 : 1441996508
Total Pages : 284 pages
Book Rating : 4.4/5 (419 download)
Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2011-04-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.
Author : Joseph Hair
Publisher : Pearson Higher Ed
ISBN 13 : 0133792684
Total Pages : 816 pages
Book Rating : 4.1/5 (337 download)
Download or read book Multivariate Data Analysis written by Joseph Hair and published by Pearson Higher Ed. This book was released on 2016-08-18 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Author : Raja Velu
Publisher : Springer Science & Business Media
ISBN 13 : 1475728530
Total Pages : 269 pages
Book Rating : 4.4/5 (757 download)
Download or read book Multivariate Reduced-Rank Regression written by Raja Velu and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model.
Author : Inge Koch
Publisher : Cambridge University Press
ISBN 13 : 0521887933
Total Pages : 531 pages
Book Rating : 4.5/5 (218 download)
Download or read book Analysis of Multivariate and High-Dimensional Data written by Inge Koch and published by Cambridge University Press. This book was released on 2014 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.
Author : Jing Wang
Publisher : Springer Nature
ISBN 13 : 9811680442
Total Pages : 277 pages
Book Rating : 4.8/5 (116 download)
Download or read book Data-Driven Fault Detection and Reasoning for Industrial Monitoring written by Jing Wang and published by Springer Nature. This book was released on 2022-01-03 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.
Author : Abdelmonem Afifi
Publisher : CRC Press
ISBN 13 : 1351788906
Total Pages : 528 pages
Book Rating : 4.3/5 (517 download)
Download or read book Practical Multivariate Analysis written by Abdelmonem Afifi and published by CRC Press. This book was released on 2019-10-16 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.
Author : Sudhanshu K. Mishra
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Representation-Constrained Canonical Correlation Analysis written by Sudhanshu K. Mishra and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical canonical correlation analysis is extremely greedy to maximize the squared correlation between two sets of variables. As a result, if one of the variables in the dataset-1 is very highly correlated with another variable in the dataset-2, the canonical correlation will be very high irrespective of the correlation among the rest of the variables in the two datasets. We intend here to propose an alternative measure of association between two sets of variables that will not permit the greed of a select few variables in the datasets to prevail upon the fellow variables so much as to deprive the latter of contributing to their representative variables or canonical variates. Our proposed Representation-Constrained Canonical correlation (RCCCA) Analysis has the Classical Canonical Correlation Analysis (CCCA) at its one end (lambda=0) and the Classical Principal Component Analysis (CPCA) at the other (as lambda tends to be very large). In between it gives us a compromise solution. By a proper choice of lambda, one can avoid hijacking of the representation issue of two datasets by a lone couple of highly correlated variables across those datasets. This advantage of the RCCCA over the CCCA deserves a serious attention by the researchers using statistical tools for data analysis.
Author : Gregory C. Reinsel
Publisher : Springer Nature
ISBN 13 : 1071627937
Total Pages : 420 pages
Book Rating : 4.0/5 (716 download)
Download or read book Multivariate Reduced-Rank Regression written by Gregory C. Reinsel and published by Springer Nature. This book was released on 2022-11-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an account of multivariate reduced-rank regression, a tool of multivariate analysis that enjoys a broad array of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods, such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models, is also discussed. This new edition incorporates Big Data methodology and its applications, as well as high-dimensional reduced-rank regression, generalized reduced-rank regression with complex data, and sparse and low-rank regression methods. Each chapter contains developments of basic theoretical results, as well as details on computational procedures, illustrated with numerical examples drawn from disciplines such as biochemistry, genetics, marketing, and finance. This book is designed for advanced students, practitioners, and researchers, who may deal with moderate and high-dimensional multivariate data. Because regression is one of the most popular statistical methods, the multivariate regression analysis tools described should provide a natural way of looking at large (both cross-sectional and chronological) data sets. This book can be assigned in seminar-type courses taken by advanced graduate students in statistics, machine learning, econometrics, business, and engineering.
Author : Michael Greenacre
Publisher : Fundacion BBVA
ISBN 13 : 8492937505
Total Pages : 336 pages
Book Rating : 4.4/5 (929 download)
Download or read book Multivariate Analysis of Ecological Data written by Michael Greenacre and published by Fundacion BBVA. This book was released on 2014-01-09 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: La diversidad biológica es fruto de la interacción entre numerosas especies, ya sean marinas, vegetales o animales, a la par que de los muchos factores limitantes que caracterizan el medio que habitan. El análisis multivariante utiliza las relaciones entre diferentes variables para ordenar los objetos de estudio según sus propiedades colectivas y luego clasificarlos; es decir, agrupar especies o ecosistemas en distintas clases compuestas cada una por entidades con propiedades parecidas. El fin último es relacionar la variabilidad biológica observada con las correspondientes características medioambientales. Multivariate Analysis of Ecological Data explica de manera completa y estructurada cómo analizar e interpretar los datos ecológicos observados sobre múltiples variables, tanto biológicos como medioambientales. Tras una introducción general a los datos ecológicos multivariantes y la metodología estadística, se abordan en capítulos específicos, métodos como aglomeración (clustering), regresión, biplots, escalado multidimensional, análisis de correspondencias (simple y canónico) y análisis log-ratio, con atención también a sus problemas de modelado y aspectos inferenciales. El libro plantea una serie de aplicaciones a datos reales derivados de investigaciones ecológicas, además de dos casos detallados que llevan al lector a apreciar los retos de análisis, interpretación y comunicación inherentes a los estudios a gran escala y los diseños complejos.
Author : Robert J. Wherry
Publisher : Academic Press
ISBN 13 : 1483266079
Total Pages : 478 pages
Book Rating : 4.4/5 (832 download)
Download or read book Contributions to Correlational Analysis written by Robert J. Wherry and published by Academic Press. This book was released on 2014-05-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributions to Correlational Analysis provides information pertinent to the fundamental aspects of correlational analysis that can be used to replace and enhance many of the parametric and nonparametric inferential statistical tests. This book discusses the basic concern of correctional analysis, which is the relationship between two sets of measure. Organized into 18 chapters, this book begins with an overview of the nature of correction analysis. This text then explains the simple linear relationships in which explains the simple linear relationships in which Y and X each consists of some single measurement per person and the relationship is assumed to be linear. Other chapters consider basic ways of expanding the process to include more or different measurements of either X or Y but with no attempt to find the best functions. This book discusses as well the topic of factor analysis. The final chapter deals with canonical correlation. This book is a valuable resource for psychologists.
Author : Richard A. Johnson
Publisher : Pearson
ISBN 13 : 9780134995397
Total Pages : 808 pages
Book Rating : 4.9/5 (953 download)
Download or read book Applied Multivariate Statistical Analysis (Classic Version) written by Richard A. Johnson and published by Pearson. This book was released on 2018-03-18 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
Author : R. Gittins
Publisher : Springer Science & Business Media
ISBN 13 : 3642698786
Total Pages : 360 pages
Book Rating : 4.6/5 (426 download)
Download or read book Canonical Analysis written by R. Gittins and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Relationships between sets of variables of different kinds are of interest in many branches of science. The question of the analysis of relationships of this sort has nevertheless rather surprisingly received less attention from statisticians and others than it would seem to deserve. Of the available methods, that address ing the question most directly is canonical correlation analysis, here referred to for convenience as canonical analysis. Yet canonical analysis is often coolly received despite a lack of suitable alternatives. The purpose of this book is to clarify just what may and what may not be accomplished by means of canoni cal analysis in one field of scientific endeavor. Canonical analysis is concerned with reducing the correlation structure be tween two (or more) sets of variables to its simplest possible form. After a review of the nature and properties of canonical analysis, an assessment of the method as an exploratory tool of use in ecological investigations is made. Applications of canonical analysis to several sets of ecological data are described and discussed with this objective in mind. The examples are drawn largely from plant ecology. The position is adopted that canonical analysis exists primarily to be used; the examples are accordingly worked through in some detail with the aim of showing how canonical analysis can contribute towards the attainment of ecological goals, as well as to indicate the kind and extent of the insight afforded.
Author : John Michael Long
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (313 download)
Download or read book AN EXTENSION OF STEPWISE VARIABLE-REDUCTION PROCEDURES FOR CANONICAL ANALYSIS written by John Michael Long and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Stanislaw Sieniutycz
Publisher : Elsevier
ISBN 13 : 0080456146
Total Pages : 810 pages
Book Rating : 4.0/5 (84 download)
Download or read book Variational and Extremum Principles in Macroscopic Systems written by Stanislaw Sieniutycz and published by Elsevier. This book was released on 2010-07-07 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen a growing trend to derive models of macroscopic phenomena encountered in the fields of engineering, physics, chemistry, ecology, self-organisation theory and econophysics from various variational or extremum principles. Through the link between the integral extremum of a functional and the local extremum of a function (explicit, for example, in the Pontryagin’s maximum principle variational and extremum principles are mutually related. Thus it makes sense to consider them within a common context. The main goal of Variational and Extremum Principles in Macroscopic Systems is to collect various mathematical formulations and examples of physical reasoning that involve both basic theoretical aspects and applications of variational and extremum approaches to systems of the macroscopic world. The first part of the book is focused on the theory, whereas the second focuses on applications. The unifying variational approach is used to derive the balance or conservation equations, phenomenological equations linking fluxes and forces, equations of change for processes with coupled transfer of energy and substance, and optimal conditions for energy management. A unique multidisciplinary synthesis of variational and extremum principles in theory and application A comprehensive review of current and past achievements in variational formulations for macroscopic processes Uses Lagrangian and Hamiltonian formalisms as a basis for the exposition of novel approaches to transfer and conversion of thermal, solar and chemical energy
Author : Keenan A. Pituch
Publisher : Routledge
ISBN 13 : 1317805925
Total Pages : 814 pages
Book Rating : 4.3/5 (178 download)
Download or read book Applied Multivariate Statistics for the Social Sciences written by Keenan A. Pituch and published by Routledge. This book was released on 2015-12-07 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.
Author : Carol S. Aneshensel
Publisher : SAGE
ISBN 13 : 1412994357
Total Pages : 473 pages
Book Rating : 4.4/5 (129 download)
Download or read book Theory-Based Data Analysis for the Social Sciences written by Carol S. Aneshensel and published by SAGE. This book was released on 2013 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
