Multivariate Distributions
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Continuous Multivariate Distributions Volume 1
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Author : Samuel Kotz
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-05
Continuous Multivariate Distributions Volume 1 written by Samuel Kotz 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 2004-04-05 with Mathematics categories.
Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications.
The Multivariate Normal Distribution
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Author : Yung Liang Tong
language : en
Publisher: Springer
Release Date : 1990
The Multivariate Normal Distribution written by Yung Liang Tong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
The multivariate normal distribution has played a predominant role in the historical development of statistical theory, and has made its appearance in various areas of applications. Although many of the results concerning the multivariate normal distribution are classical, there are important new results which have been reported recently in the literature but cannot be found in most books on multivariate analysis. These results are often obtained by showing that the multivariate normal density function belongs to certain large families of density functions. Thus, useful properties of such families immedi ately hold for the multivariate normal distribution. This book attempts to provide a comprehensive and coherent treatment of the classical and new results related to the multivariate normal distribution. The material is organized in a unified modern approach, and the main themes are dependence, probability inequalities, and their roles in theory and applica tions. Some general properties of a multivariate normal density function are discussed, and results that follow from these properties are reviewed exten sively. The coverage is, to some extent, a matter of taste and is not intended to be exhaustive, thus more attention is focused on a systematic presentation of results rather than on a complete listing of them.
Multivariate Statistical Simulation
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Author : Mark E. Johnson
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-11
Multivariate Statistical Simulation written by Mark E. Johnson 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 2013-11-11 with Mathematics categories.
Provides state-of-the-art coverage for the researcher confronted with designing and executing a simulation study using continuous multivariate distributions. Concise writing style makes the book accessible to a wide audience. Well-known multivariate distributions are described, emphasizing a few representative cases from each distribution. Coverage includes Pearson Types II and VII elliptically contoured distributions, Khintchine distributions, and the unifying class for the Burr, Pareto, and logistic distributions. Extensively illustrated--the figures are unique, attractive, and reveal very nicely what distributions ``look like.'' Contains an extensive and up-to-date bibliography culled from journals in statistics, operations research, mathematics, and computer science.
Probability Inequalities In Multivariate Distributions
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Author : Y. L. Tong
language : en
Publisher: Academic Press
Release Date : 2014-07-10
Probability Inequalities In Multivariate Distributions written by Y. L. Tong and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-10 with Mathematics categories.
Probability Inequalities in Multivariate Distributions is a comprehensive treatment of probability inequalities in multivariate distributions, balancing the treatment between theory and applications. The book is concerned only with those inequalities that are of types T1-T5. The conditions for such inequalities range from very specific to very general. Comprised of eight chapters, this volume begins by presenting a classification of probability inequalities, followed by a discussion on inequalities for multivariate normal distribution as well as their dependence on correlation coefficients. The reader is then introduced to inequalities for other well-known distributions, including the multivariate distributions of t, chi-square, and F; inequalities for a class of symmetric unimodal distributions and for a certain class of random variables that are positively dependent by association or by mixture; and inequalities obtainable through the mathematical tool of majorization and weak majorization. The book also describes some distribution-free inequalities before concluding with an overview of their applications in simultaneous confidence regions, hypothesis testing, multiple decision problems, and reliability and life testing. This monograph is intended for mathematicians, statisticians, students, and those who are primarily interested in inequalities.
Symmetric Multivariate And Related Distributions
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Author : Kai-Tai Fang
language : en
Publisher: CRC Press
Release Date : 2018-01-18
Symmetric Multivariate And Related Distributions written by Kai-Tai Fang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Mathematics categories.
Since the publication of the by now classical Johnson and Kotz Continuous Multivariate Distributions (Wiley, 1972) there have been substantial developments in multivariate distribution theory especially in the area of non-normal symmetric multivariate distributions. The book by Fang, Kotz and Ng summarizes these developments in a manner which is accessible to a reader with only limited background (advanced real-analysis calculus, linear algebra and elementary matrix calculus). Many of the results in this field are due to Kai-Tai Fang and his associates and appeared in Chinese publications only. A thorough literature search was conducted and the book represents the latest work - as of 1988 - in this rapidly developing field of multivariate distributions. The authors are experts in statistical distribution theory.
Current Index To Statistics Applications Methods And Theory
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Author :
language : en
Publisher:
Release Date : 1999
Current Index To Statistics Applications Methods And Theory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematical statistics categories.
The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Stochastic Modelling Of River Morphodynamics
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Author : Saskia van Vuren
language : en
Publisher: Delft University Press
Release Date : 2005
Stochastic Modelling Of River Morphodynamics written by Saskia van Vuren and has been published by Delft University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Science categories.
Stochastic modelling of river morphology and its potential in present-day river management practice is the topic of this thesis. In summary, this thesis shows how to analyse the stochastic nature of river morphology by means of Monte Carlo Simulation. It provides insight into the uncertainty sources that contribute most to the stochastic morphodynamic river behaviour. Furthermore, three applications illustrate the potential of a stochastic model approach in river management practice. The conclusion can be drawn that the use of this 'computation-intensive' approach adds value to river engineering and management practice
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.
Copulae And Multivariate Probability Distributions In Finance
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Author : Alexandra Dias
language : en
Publisher: Routledge
Release Date : 2013-08-21
Copulae And Multivariate Probability Distributions In Finance written by Alexandra Dias and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-21 with Business & Economics categories.
Portfolio theory and much of asset pricing, as well as many empirical applications, depend on the use of multivariate probability distributions to describe asset returns. Traditionally, this has meant the multivariate normal (or Gaussian) distribution. More recently, theoretical and empirical work in financial economics has employed the multivariate Student (and other) distributions which are members of the elliptically symmetric class. There is also a growing body of work which is based on skew-elliptical distributions. These probability models all exhibit the property that the marginal distributions differ only by location and scale parameters or are restrictive in other respects. Very often, such models are not supported by the empirical evidence that the marginal distributions of asset returns can differ markedly. Copula theory is a branch of statistics which provides powerful methods to overcome these shortcomings. This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. Multivariate non-Gaussian dependence is a fact of life for many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features of financial data. This book was originally published as a special issue of the European Journal of Finance.
Linear And Graphical Models
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Author : Heidi H. Andersen
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-05-19
Linear And Graphical Models written by Heidi H. Andersen 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 1995-05-19 with Mathematics categories.
In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.