Bilinear Regression Analysis
DOWNLOAD
Download Bilinear Regression Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Bilinear Regression Analysis 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
Bilinear Regression Analysis
DOWNLOAD
Author : Dietrich Von Rosen
language : en
Publisher:
Release Date : 2018
Bilinear Regression Analysis written by Dietrich Von Rosen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Algebra categories.
This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph. D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
Bilinear Regression Analysis
DOWNLOAD
Author : Dietrich von Rosen
language : en
Publisher: Springer
Release Date : 2018-08-02
Bilinear Regression Analysis written by Dietrich von Rosen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-02 with Mathematics categories.
This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
Bilinear And Trilinear Regression Models With Structured Covariance Matrices
DOWNLOAD
Author : Joseph Nzabanita
language : en
Publisher: Linköping University Electronic Press
Release Date : 2015-05-21
Bilinear And Trilinear Regression Models With Structured Covariance Matrices written by Joseph Nzabanita and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-21 with Matrices categories.
This thesis focuses on the problem of estimating parameters in bilinear and trilinear regression models in which random errors are normally distributed. In these models the covariance matrix has a Kronecker product structure and some factor matrices may be linearly structured. The interest of considering various structures for the covariance matrices in different statistical models is partly driven by the idea that altering the covariance structure of a parametric model alters the variances of the model’s estimated mean parameters. Firstly, the extended growth curve model with a linearly structured covariance matrix is considered. The main theme is to find explicit estimators for the mean and for the linearly structured covariance matrix. We show how to decompose the residual space, the orthogonal complement to the mean space, into appropriate orthogonal subspaces and how to derive explicit estimators of the covariance matrix from the sum of squared residuals obtained by projecting observations on those subspaces. Also an explicit estimator of the mean is derived and some properties of the proposed estimators are studied. Secondly, we study a bilinear regression model with matrix normally distributed random errors. For those models, the dispersion matrix follows a Kronecker product structure and it can be used, for example, to model data with spatio-temporal relationships. The aim is to estimate the parameters of the model when, in addition, one covariance matrix is assumed to be linearly structured. On the basis of n independent observations from a matrix normal distribution, estimating equations, a flip-flop relation, are established. At last, the models based on normally distributed random third order tensors are studied. These models are useful in analyzing 3-dimensional data arrays. In some studies the analysis is done using the tensor normal model, where the focus is on the estimation of the variance-covariance matrix which has a Kronecker structure. Little attention is paid to the structure of the mean, however, there is a potential to improve the analysis by assuming a structured mean. We formally introduce a 2-fold growth curve model by assuming a trilinear structure for the mean in the tensor normal model and propose an estimation algorithm for parameters. Also some extensions are discussed.
Handbook Of Near Infrared Analysis
DOWNLOAD
Author : Donald A. Burns
language : en
Publisher: CRC Press
Release Date : 2007-09-07
Handbook Of Near Infrared Analysis written by Donald A. Burns and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-07 with Science categories.
Fast, inexpensive, and easy-to-use, near-infrared (NIR) spectroscopy can be used to analyze small samples of virtually any composition. The Handbook of Near Infrared Analysis, Third Edition explains how to perform accurate as well as time- and cost-effective analyses across a growing spectrum of disciplines. Presenting nearly 50% new and re
Statistical Parametric Mapping The Analysis Of Functional Brain Images
DOWNLOAD
Author : William D. Penny
language : en
Publisher: Elsevier
Release Date : 2011-04-28
Statistical Parametric Mapping The Analysis Of Functional Brain Images written by William D. Penny and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-28 with Psychology categories.
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Handbook Of Near Infrared Analysis Second Edition
DOWNLOAD
Author : Donald A. Burns
language : en
Publisher: CRC Press
Release Date : 2001-06-28
Handbook Of Near Infrared Analysis Second Edition written by Donald A. Burns and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-06-28 with Science categories.
With contributions from over 40 experts in the field, this reference presents comprehensive, single-source coverage of the instrumentation, computerization, calibration, and methods development of NIR spectroscopy. It provides novel applications for accurate time- and cost-effective analyses of pharmaceuticals, polymers, textiles, agricultural products, dairy products, foods, and beverages. Emphasizing trends in sample preparation, the book covers historical development, calibration transfer, biomedical applications, plastics, and counterfeiting; on-line, in-line, and at-line analyses for process control, multilinear regression and principal component analysis, and more.
Contemporary Experimental Design Multivariate Analysis And Data Mining
DOWNLOAD
Author : Jianqing Fan
language : en
Publisher: Springer Nature
Release Date : 2020-05-22
Contemporary Experimental Design Multivariate Analysis And Data Mining written by Jianqing Fan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with Mathematics categories.
The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features four review papers on Professor Fang’s numerous contributions to the fields of experimental design, multivariate analysis, data mining and education. It also contains twenty research articles contributed by prominent and active figures in their fields. The articles cover a wide range of important topics such as experimental design, multivariate analysis, data mining, hypothesis testing and statistical models.
Handbook Of Research On Trends And Digital Advances In Engineering Geology
DOWNLOAD
Author : Ceryan, Nurcihan
language : en
Publisher: IGI Global
Release Date : 2017-07-12
Handbook Of Research On Trends And Digital Advances In Engineering Geology written by Ceryan, Nurcihan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Science categories.
Engineering geologists face the task of addressing geological factors that can affect planning with little time and with few resources. A solution is using the right tools to save time searching for answers and devote attention to making critical engineering decisions. The Handbook of Research on Trends and Digital Advances in Engineering Geology is an essential reference source for the latest research on new trends, technology, and computational methods that can model engineering phenomena automatically. Featuring exhaustive coverage on a broad range of topics and perspectives such as acoustic energy, landslide mapping, and natural hazards, this publication is ideally designed for academic scientists, industry and applied researchers, and policy and decision makers seeking current research on new tools to aid in timely decision-making of critical engineering situations.
Methodology And Applications Of Statistics
DOWNLOAD
Author : Barry C. Arnold
language : en
Publisher: Springer Nature
Release Date : 2022-01-04
Methodology And Applications Of Statistics written by Barry C. Arnold and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-04 with Mathematics categories.
Dedicated to one of the most outstanding researchers in the field of statistics, this volume in honor of C.R. Rao, on the occasion of his 100th birthday, provides a bird’s-eye view of a broad spectrum of research topics, paralleling C.R. Rao’s wide-ranging research interests. The book’s contributors comprise a representative sample of the countless number of researchers whose careers have been influenced by C.R. Rao, through his work or his personal aid and advice. As such, written by experts from more than 15 countries, the book’s original and review contributions address topics including statistical inference, distribution theory, estimation theory, multivariate analysis, hypothesis testing, statistical modeling, design and sampling, shape and circular analysis, and applications. The book will appeal to statistics researchers, theoretical and applied alike, and PhD students. Happy Birthday, C.R. Rao!
Partial Least Squares Regression
DOWNLOAD
Author : R. Dennis Cook
language : en
Publisher: CRC Press
Release Date : 2024-07-22
Partial Least Squares Regression written by R. Dennis Cook and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Mathematics categories.
Partial least squares (PLS) regression is, at its historical core, a black-box algorithmic method for dimension reduction and prediction based on an underlying linear relationship between a possibly vector-valued response and a number of predictors. Through envelopes, much more has been learned about PLS regression, resulting in a mass of information that allows an envelope bridge that takes PLS regression from a black-box algorithm to a core statistical paradigm based on objective function optimization and, more generally, connects the applied sciences and statistics in the context of PLS. This book focuses on developing this bridge. It also covers uses of PLS outside of linear regression, including discriminant analysis, non-linear regression, generalized linear models and dimension reduction generally. Key Features: • Showcases the first serviceable method for studying high-dimensional regressions. • Provides necessary background on PLS and its origin. • R and Python programs are available for nearly all methods discussed in the book. R. Dennis Cook is Professor Emeritus, School of Statistics, University of Minnesota. His research areas include dimension reduction, linear and nonlinear regression, experimental design, statistical diagnostics, statistical graphics, and population genetics. Perhaps best known for "Cook’s Distance," a now ubiquitous statistical method, he has authored over 250 research articles, two textbooks and three research monographs. He is a five-time recipient of the Jack Youden Prize for Best Expository Paper in Technometrics as well as the Frank Wilcoxon Award for Best Technical Paper. He received the 2005 COPSS Fisher Lecture and Award and is a Fellow of ASA and IMS. Liliana Forzani is Full Professor, School of Chemical Engineering, National University of Litoral and principal researcher of CONICET (National Scientific and Technical Research Council), Argentina. Her contributions are in mathematical statistics, especially sufficient dimension reduction, abundance in regression and statistics for chemometrics. She established the first research group in statistics at her university after receiving her Ph. D in Statistics at the University of Minnesota. She has authored over 75 research articles in mathematics and statistics, and was recipient of the L‘Oreal-Unesco-Conicet prize for Women in science.