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Book Multi set Nonlinear Canonical Correlation Analysis Via the Burt matrix

Download or read book Multi set Nonlinear Canonical Correlation Analysis Via the Burt matrix written by Robert Jaap Walter Tijssen and published by . This book was released on 1988 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Multiway Data Analysis

Download or read book Multiway Data Analysis written by R. Coppi and published by North Holland. This book was released on 1989 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects together 45 papers covering various aspects of the analysis of multiway data arrays. Mathematical properties of three-way and multiway arrays are investigated and their utilization for the statistical interpretation of complex data sets is emphasized. The volume is divided into 5 chapters. A specific introduction to each chapter has been prepared by the Editorial Board. Different methods of analysis are considered including: longitudinal and multimode factor analysis, generalized canonical analysis, multidimensional scaling, multiway classification techniques, model based approaches. The reader can find many original contributions to this area, as well as interesting applications in several fields of research such as psychology, economics, sociology and bio-medicine.

Book Multiple Correspondence Analysis and Related Methods

Download or read book Multiple Correspondence Analysis and Related Methods written by Michael Greenacre and published by CRC Press. This book was released on 2006-06-23 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su

Book Canonical Correlation Analysis

Download or read book Canonical Correlation Analysis written by Bruce Thompson and published by SAGE. This book was released on 1984-11 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances both in statistical methodology and in computer automation are making canonical correlation analysis available to more and more researchers. In an essentially nonmathematical presentation that provides numerous examples, this volume explains the basic features of this sophisticated technique. Learn more about "The Little Green Book" - QASS Series! Click Here

Book Nonlinear Canonical Correlation Analysis with K Sets of Variables

Download or read book Nonlinear Canonical Correlation Analysis with K Sets of Variables written by Eeke van der Burg and published by . This book was released on 1987 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Statistical Theory and Method Abstracts

Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 1990 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Canonical Auto and Cross Correlations of Multivariate Time Series

Download or read book Canonical Auto and Cross Correlations of Multivariate Time Series written by Marcia W. Bulach and published by Universal-Publishers. This book was released on 1999 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of Multivariate Time Series has always been more difficult at the modeling stage than the univariate case. Identification of a suitable model, questions of stability, and the difficulties of prediction are well recognised. A variety of methods appear to be worth examining. This thesis is concerned with the proposal of an useful tool which is to apply canonical analysis to a realisation of a Multivariate Time Series and concentrates it's attention on k-variate ARMA(p, q) models. The multivariate series is partitioned into two overlapping or non-overlapping sets of different sizes. The left set is kept at lag 0 (without loss of generality) and the right set at a sequence of lags s=0,1, ... . The model includes the possibility that the same subset of variables belong to the left set at lag 0 and to the right set at lag s. A technique for dimension reduction is suggested. We tried to elucidate identification and the internal structure of time-dependence at several pairs of lags as a tool for identification. As the technique suggested provide a method of investigation of patterns of interrelations between two multivariate sets or subsets of variables with a joint distribution, it is an efficient tool for use in multivariate series of economic data. A review of the basic models of Multivariate Time Series is given and their canonical auto and cross correlation analysis is presented. In order to study the asymptotic distribution, several Monte Carlo experiments were necessary. We attempted to provide information through simulation about the distributional and other statistical properties for the canonical statistics obtained by our procedures. New software is provided and data experience is given. The first computer program provides us with information, graphs for the canonical auto and cross correlations, test statistics for the 'useful' canonical auto and cross correlations as well as the left and right eigenvectors, left and right intraset and interset matrices of correlations, proportions of variances extracted by the canonical variates of the left and of the right sets and left and right redundancies for lags s=0,1, ... .The second program gives similar calculations for the k-variate ARMA(p, q) models when the matrices of parameters and variance-covariance matrix of the error are known. The third program provides us with the mean value, minimum and maximum values, excess kurtosis, histogram and cumulative distribution for each one of the canonical auto and cross correlations at every lag s calculated from several simulations of Monte Carlo generated k-variate ARMA(p, q) models when the matrices of parameters and variance-covariance matrix of the error are given or when they are generated. The second part of the thesis is devoted to the generalisation of the robust and practically useful univariate Holt-Winters model. We developed formula for the Multivariate Additive Holt-Winters (Seasonal and Non-Seasonal) to the point of application and its reduction to Moving Average form. New software is produced. The link between the two main themes consists on the canonical analysis of a Multivariate Holt-Winters from its reduced MA form and reducing its dimension as well as detecting the basic linear relationships between variables, between and within several lags. We also attempted to investigate the effect of outliers, the removal of non-stationary trends via cubic spline fitting, differencing as well as transformations such as loge (data).

Book Nonlinear Canonical Correlation Analysis of Multiway Data

Download or read book Nonlinear Canonical Correlation Analysis of Multiway Data written by Eeke van der Burg and published by . This book was released on 1988 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Some Aspects of Canonical Correlation Analysis

Download or read book Some Aspects of Canonical Correlation Analysis written by Yu Shyr and published by . This book was released on 1994 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Canonical Correlation and Correspondence Analysis of Longitudinal Data

Download or read book Canonical Correlation and Correspondence Analysis of Longitudinal Data written by Jayesh Srivastava and published by . This book was released on 2007 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assessing the relationship between two sets of multivariate vectors is an important problem in statistics. Canonical correlation coefficients are used to study these relationships. Canonical correlation analysis (CCA) is a general multivariate method that is mainly used to study relationships when both sets of variables are quantitative. When the variables are qualitative (categorical), a technique called correspondence analysis (CA) is used. Canonical correspondence analysis (CCPA) is used to deal with the case when one set of variables is categorical and the other set is quantitative. By exploiting the interrelationships between these three techniques we first provide a theoretical basis for CCPA.

Book Non linear Canonical Correlation with M Sets of Variables

Download or read book Non linear Canonical Correlation with M Sets of Variables written by Eeke van der Burg and published by . This book was released on 1984 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Mathematical Reviews

Download or read book Mathematical Reviews written by and published by . This book was released on 1997 with total page 922 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Multilevel Probabilistic Canonical Correlation Analysis for Integrative Analysis of Multi Omics Data with Repeated Measurements

Download or read book Multilevel Probabilistic Canonical Correlation Analysis for Integrative Analysis of Multi Omics Data with Repeated Measurements written by Yuna Kim and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-omics data have been used to characterize covariation in multiple biological profiles, allowing for a more comprehensive understanding of complex biological processes. Moreover, the reduction in costs of high-throughput technologies has further broadened the scope of multi-omics studies enabling the collection of repeated measurements or longitudinal data. While mixed effects models are widely used in repeated measures single omics applications, their use in applications for integrative analyses of multilevel structured multi-omics data is less developed. Probabilistic canonical correlation analysis (PCCA) considers probability models for jointly studying the relations among two sets of data, collected on the same set of samples. In this dissertation, we propose (1) multilevel probabilistic CCA that extends PCCA to repeated measurements data to help learn the underlying shared structures between two omics data sources simultaneously at both the within- and between-subject levels, (2) sparse multilevel PCCA for a variable selection and better interpretability by imposing sparsity on the feature loadings using adaptive lasso, and (3) sparse multilevel multiple PCCA to facilitate the integration of more than two sets of variables. We examine our proposed methods' operating characteristics and variable selection performance and compare our approach with the standard integration methods through simulation studies. Finally, our methods are illustrated with an application to real data from a study, which investigated the associations between advanced colorectal adenoma, pattern recognition receptor genes (PRRs), and gut microbiota, for integration of gene expression and microbiome data.

Book Canonical Correlation Analysis

Download or read book Canonical Correlation Analysis written by Thompson and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book SAS STAT 9  3 User s Guide

    Book Details:
  • Author : Sas Institute
  • Publisher :
  • Release : 2011-07
  • ISBN : 9781607646341
  • Pages : 0 pages

Download or read book SAS STAT 9 3 User s Guide written by Sas Institute and published by . This book was released on 2011-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GLIMMIX procedure fits and analyzes generalized linear mixed models (GLMM), models with random effects for data that can be nonnormally distributed. This title is also available online.

Book The SAGE Handbook of Quantitative Methodology for the Social Sciences

Download or read book The SAGE Handbook of Quantitative Methodology for the Social Sciences written by David Kaplan and published by SAGE Publications. This book was released on 2004-06-21 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: Click ′Additional Materials′ for downloadable samples "The 24 chapters in this Handbook span a wide range of topics, presenting the latest quantitative developments in scaling theory, measurement, categorical data analysis, multilevel models, latent variable models, and foundational issues. Each chapter reviews the historical context for the topic and then describes current work, including illustrative examples where appropriate. The level of presentation throughout the book is detailed enough to convey genuine understanding without overwhelming the reader with technical material. Ample references are given for readers who wish to pursue topics in more detail. The book will appeal to both researchers who wish to update their knowledge of specific quantitative methods, and students who wish to have an integrated survey of state-of- the-art quantitative methods." —Roger E. Millsap, Arizona State University "This handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential reference for social science researchers as an introduction to methods and quantitative concepts of great use." —Irini Moustaki, London School of Economics, U.K. "David Kaplan and SAGE Publications are to be congratulated on the development of a new handbook on quantitative methods for the social sciences. The Handbook is more than a set of methodologies, it is a journey. This methodological journey allows the reader to experience scaling, tests and measurement, and statistical methodologies applied to categorical, multilevel, and latent variables. The journey concludes with a number of philosophical issues of interest to researchers in the social sciences. The new Handbook is a must purchase." —Neil H. Timm, University of Pittsburgh The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource. The handbook is divided into six sections: • Scaling • Testing and Measurement • Models for Categorical Data • Models for Multilevel Data • Models for Latent Variables • Foundational Issues These sections, comprising twenty-four chapters, address topics in scaling and measurement, advances in statistical modeling methodologies, and broad philosophical themes and foundational issues that transcend many of the quantitative methodologies covered in the book. The Handbook is indispensable to the teaching, study, and research of quantitative methods and will enable readers to develop a level of understanding of statistical techniques commensurate with the most recent, state-of-the-art, theoretical developments in the field. It provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method, depending on the data and distinct research situation.