Topics In Reduced Rank Regression
DOWNLOAD
Download Topics In Reduced Rank Regression PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Topics In Reduced Rank Regression book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Topics In Reduced Rank Regression
DOWNLOAD
Author : Rajabather Palani Velu
language : en
Publisher:
Release Date : 1983
Topics In Reduced Rank Regression written by Rajabather Palani Velu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Ranking and selection (Statistics) categories.
Multivariate Reduced Rank Regression
DOWNLOAD
Author : Gregory C. Reinsel
language : en
Publisher: Springer Nature
Release Date : 2022-11-30
Multivariate Reduced Rank Regression written by Gregory C. Reinsel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Mathematics categories.
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.
Multivariate Reduced Rank Regression
DOWNLOAD
Author : Raja Velu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Multivariate Reduced Rank Regression written by Raja Velu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
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.
Multivariate Reduced Rank Regression
DOWNLOAD
Author : Raja Velu
language : en
Publisher: Springer
Release Date : 1998-09-18
Multivariate Reduced Rank Regression written by Raja Velu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-09-18 with Mathematics categories.
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.
Trends And Topics In Computer Vision
DOWNLOAD
Author : Kiriakos N. Kutulakos
language : en
Publisher: Springer
Release Date : 2013-01-18
Trends And Topics In Computer Vision written by Kiriakos N. Kutulakos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Computers categories.
The two volumes LNCS 6553 and 6554 constitute the refereed post-proceedings of 7 workshops held in conjunction with the 11th European Conference on Computer Vision, held in Heraklion, Crete, Greece in September 2010. The 62 revised papers presented together with 2 invited talks were carefully reviewed and selected from numerous submissions. The first volume contains 26 revised papers and 2 invited talks selected from the following workshops: First International Workshop on Parts and Attributes; Third Workshop on Human Motion Understanding, Modeling, Capture and Animation; and International Workshop on Sign, Gesture and Activity (SGA 2010).
Reduced Rank Regression
DOWNLOAD
Author : Heinz Schmidli
language : en
Publisher: Physica
Release Date : 1995-07-27
Reduced Rank Regression written by Heinz Schmidli and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-07-27 with Business & Economics categories.
Reduced rank regression is widely used in statistics to model multivariate data. In this monograph, theoretical and data analytical approaches are developed for the application of reduced rank regression in multivariate prediction problems. For the first time, both classical and Bayesian inference is discussed, using recently proposed procedures such as the ECM-algorithm and the Gibbs sampler. All methods are motivated and illustrated by examples taken from the area of quantitative structure-activity relationships (QSAR).
Multivariate Observations
DOWNLOAD
Author : George A. F. Seber
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25
Multivariate Observations written by George A. F. Seber and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "In recent years many monographs have been published on specialized aspects of multivariate data-analysis–on cluster analysis, multidimensional scaling, correspondence analysis, developments of discriminant analysis, graphical methods, classification, and so on. This book is an attempt to review these newer methods together with the classical theory. . . . This one merits two cheers." –J. C. Gower, Department of Statistics Rothamsted Experimental Station, Harpenden, U.K. Review in Biometrics, June 1987 Multivariate Observations is a comprehensive sourcebook that treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high-dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. The book includes many numerical examples and over 1,100 references.
Biplots
DOWNLOAD
Author : J.C. Gower
language : en
Publisher: CRC Press
Release Date : 1995-12-01
Biplots written by J.C. Gower and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-12-01 with Mathematics categories.
Biplots are the multivariate analog of scatter plots, approximating the multivariate distribution of a sample in a few dimensions to produce a graphic display. In addition, they superimpose representations of the variables on this display so that the relationships between the sample and the variable can be studied. Like scatter plots, biplots are useful for detecting patterns and for displaying the results found by more formal methods of analysis. In recent years the theory of biplots has been considerably extended. The approach adopted here is geometric, permitting a natural integration of well-known methods, such as components analysis, correspondence analysis, and canonical variate analysis as well as some newer and less well-known methods, such as nonlinear biplots and biadditive models.
Advanced Econometric Theory
DOWNLOAD
Author : John Chipman
language : en
Publisher: Routledge
Release Date : 2013-03-01
Advanced Econometric Theory written by John Chipman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-01 with Business & Economics categories.
When learning econometrics, what better way than to be taught by one of its masters. In this significant new volume, John Chipman, the eminence grise of econometrics, presents his classic lectures in econometric theory. Starting with the linear regression model, least squares, Gauss-Markov theory and the first principals of econometrics, this book guides the introductory student to an advanced stage of ability. The text covers multicollinearity and reduced-rank estimation, the treatment of linear restrictions and minimax estimation. Also included are chapters on the autocorrelation of residuals and simultaneous-equation estimation. By the end of the text, students will have a solid grounding in econometrics. Despite the frequent complexity of the subject matter, Chipman's clear explanations, concise prose and sharp analysis make this book stand out from others in the field. With mathematical rigor sharpened by a lifetime of econometric analysis, this significant volume is sure to become a seminal and indispensable text in this area.
Machine Learning Low Rank Approximations And Reduced Order Modeling In Computational Mechanics
DOWNLOAD
Author : Felix Fritzen
language : en
Publisher: MDPI
Release Date : 2019-09-18
Machine Learning Low Rank Approximations And Reduced Order Modeling In Computational Mechanics written by Felix Fritzen and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-18 with Technology & Engineering categories.
The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The articles contained in this compilation were presented at the EUROMECH Colloquium 597, « Reduced Order Modeling in Mechanics of Materials », held in Bad Herrenalb, Germany, from August 28th to August 31th 2018. In this book, Artificial Neural Networks are coupled to physics-based models. The tensor format of simulation data is exploited in surrogate models or for data pruning. Various reduced order models are proposed via machine learning strategies applied to simulation data. Since reduced order models have specific approximation errors, error estimators are also proposed in this book. The proposed numerical examples are very close to engineering problems. The reader would find this book to be a useful reference in identifying progress in machine learning and reduced order modeling for computational mechanics.