Matrix Variate Distributions
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Matrix Variate Distributions
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Author : A K Gupta
language : en
Publisher: CRC Press
Release Date : 2018-05-02
Matrix Variate Distributions written by A K Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-02 with Mathematics categories.
Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods. Until now, however, most of the material on random matrices could only be found scattered in various statistical journals. Matrix Variate Distributions gathers and systematically presents most of the recent developments in continuous matrix variate distribution theory and includes new results. After a review of the essential background material, the authors investigate the range of matrix variate distributions, including: matrix variate normal distribution Wishart distribution Matrix variate t-distribution Matrix variate beta distribution F-distribution Matrix variate Dirichlet distribution Matrix quadratic forms With its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.
Contributions To Complex Matrix Variate Distributions Theory
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Author : Daya Krishna Nagar
language : en
Publisher: Universidad de Antioquia
Release Date : 2009
Contributions To Complex Matrix Variate Distributions Theory written by Daya Krishna Nagar and has been published by Universidad de Antioquia this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Distribution (Probability theory) categories.
"Random matrices (real or complex) play an important role in the study of multivariate statistical methods. They have been found useful in physics, engineering, economics, psychology and other fields of investigation. Contributions to Complex Matrix Variate Distribution Theory gives a comprehensive coverage of complex random matrices, and defines a number of new complex matrix variate distributions. It also gathers and systematiclly [sic] presents several results on zonal polynomials, invariant polynomials and hypergeometric functions of Hermitian matrices which until now could only be found scattered in various mathematical or statistical journals. This book provides a compact self-contained introduction to the complex matrix variate distribution theory and includes new results that will be a useful source to all those working in the area, stimulate further research, and help advance this field. This book, valuable to researchers, graduate students, and instructors in multivariate statistical analysis, will also interest researchers in a variety of areas including physicists, engineers, psychometricians, and econometricians."--Back cover
Multivariate Normal Distribution The Theory And Applications
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Author : Thu Pham-gia
language : en
Publisher: World Scientific
Release Date : 2021-05-05
Multivariate Normal Distribution The Theory And Applications written by Thu Pham-gia and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-05 with Business & Economics categories.
This book provides the reader with user-friendly applications of normal distribution. In several variables it is called the multinormal distribution which is often handled using matrices for convenience. The author seeks to make the arguments less abstract and hence, starts with the univariate case and moves progressively toward the vector and matrix cases. The approach used in the book is a gradual one, going from one scalar variable to a vector variable and to a matrix variable. The author presents the unified aspect of normal distribution, as well as addresses several other issues, including random matrix theory in physics. Other well-known applications, such as Herrnstein and Murray's argument that human intelligence is substantially influenced by both inherited and environmental factors, will be discussed in this book. It is a better predictor of many personal dynamics — including financial income, job performance, birth out of wedlock, and involvement in crime — than are an individual's parental socioeconomic status, or education level, and deserve to be mentioned and discussed.
Intuition In Psychotherapy And Counselling
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Author : Rachel Charles
language : en
Publisher: John Wiley & Sons
Release Date : 2004-10
Intuition In Psychotherapy And Counselling written by Rachel Charles 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 2004-10 with Psychology categories.
Since nonverbal messages have been shown to dominate interpersonal communication, and since their cues are gathered intuitively, it is clearly a distinct advantage for therapists and counsellors to be familiar with this phenomenon. Based on original research into intuition within clinical practice, Rachel Charles provides in-depth explanations of the process, appropriately illustrated with models and case histories. This includes intuition's allo-logical and global aspects, its relationship to empathy and its links with spiritual practice. A theoretical framework is thus provided for its comprehension and teaching. While some people are naturally more intuitive than others, the author makes a number of practical recommendations whereby the faculty of intuition can be cultivated by therapists, increasing receptivity to unconscious messages and helping the client to achieve insight. Clinicians, training institutes, their tutors and students, and indeed anyone working with people, will find this book a valuable resource for the enhancement of professional practice.
Shrinkage Estimation For Mean And Covariance Matrices
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Author : Hisayuki Tsukuma
language : en
Publisher: Springer
Release Date : 2020-04-17
Shrinkage Estimation For Mean And Covariance Matrices written by Hisayuki Tsukuma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-17 with Medical categories.
This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal distribution models. More specifically, it presents recent techniques and results in estimation of mean and covariance matrices with a high-dimensional setting that implies singularity of the sample covariance matrix. Such high-dimensional models can be analyzed by using the same arguments as for low-dimensional models, thus yielding a unified approach to both high- and low-dimensional shrinkage estimations. The unified shrinkage approach not only integrates modern and classical shrinkage estimation, but is also required for further development of the field. Beginning with the notion of decision-theoretic estimation, this book explains matrix theory, group invariance, and other mathematical tools for finding better estimators. It also includes examples of shrinkage estimators for improving standard estimators, such as least squares, maximum likelihood, and minimum risk invariant estimators, and discusses the historical background and related topics in decision-theoretic estimation of parameter matrices. This book is useful for researchers and graduate students in various fields requiring data analysis skills as well as in mathematical statistics.
Elliptically Contoured Models In Statistics
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Author : Arjun K. Gupta
language : en
Publisher: Springer
Release Date : 2012-09-21
Elliptically Contoured Models In Statistics written by Arjun K. Gupta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-21 with Mathematics categories.
In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. Fang, Kotz, and Ng presented a systematic study of multivariate elliptical distributions, however, they did not discuss the matrix variate case. Recently Fang and Zhang have summarized the results of generalized multivariate analysis which include vector as well as the matrix variate distributions. On the other hand, Fang and Anderson collected research papers on matrix variate elliptical distributions, many of them published for the first time in English. They published very rich material on the topic, but the results are given in paper form which does not provide a unified treatment of the theory. Therefore, it seemed appropriate to collect the most important results on the theory of matrix variate elliptically contoured distributions available in the literature and organize them in a unified manner that can serve as an introduction to the subject. The book will be useful for researchers, teachers, and graduate students in statistics and related fields whose interests involve multivariate statistical analysis. Parts of this book were presented by Arjun K Gupta as a one semester course at Bowling Green State University. Some new results have also been included which generalize the results in Fang and Zhang. Knowledge of matrix algebra and statistics at the level of Anderson is assumed. However, Chapter 1 summarizes some results of matrix algebra.
Multivariate T Distributions And Their Applications
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Author : Samuel Kotz
language : en
Publisher: Cambridge University Press
Release Date : 2004-02-16
Multivariate T Distributions And Their Applications written by Samuel Kotz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-02-16 with Mathematics categories.
Almost all the results available in the literature on multivariate t-distributions published in the last 50 years are now collected together in this comprehensive reference. Because these distributions are becoming more prominent in many applications, this book is a must for any serious researcher or consultant working in multivariate analysis and statistical distributions. Much of this material has never before appeared in book form. The first part of the book emphasizes theoretical results of a probabilistic nature. In the second part of the book, these are supplemented by a variety of statistical aspects. Various generalizations and applications are dealt with in the final chapters. The material on estimation and regression models is of special value for practitioners in statistics and economics. A comprehensive bibliography of over 350 references is included.
Recent Perspectives In Random Matrix Theory And Number Theory
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Author : F. Mezzadri
language : en
Publisher: Cambridge University Press
Release Date : 2005-06-21
Recent Perspectives In Random Matrix Theory And Number Theory written by F. Mezzadri and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-21 with Mathematics categories.
Provides a grounding in random matrix techniques applied to analytic number theory.
Innovations In Multivariate Statistical Modeling
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Author : Andriëtte Bekker
language : en
Publisher: Springer Nature
Release Date : 2022-12-15
Innovations In Multivariate Statistical Modeling written by Andriëtte Bekker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-15 with Mathematics categories.
Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.
Multivariate Statistical Analysis In The Real And Complex Domains
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Author : Arak M. Mathai
language : en
Publisher: Springer Nature
Release Date : 2022-10-04
Multivariate Statistical Analysis In The Real And Complex Domains written by Arak M. Mathai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-04 with Mathematics categories.
This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.