Theory Of Multivariate Statistics
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Theory Of Multivariate Statistics
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Author : Martin Bilodeau
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-20
Theory Of Multivariate Statistics written by Martin Bilodeau 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 2008-01-20 with Mathematics categories.
Intended as a textbook for students taking a first graduate course in the subject, as well as for the general reference of interested research workers, this text discusses, in a readable form, developments from recently published work on certain broad topics not otherwise easily accessible, such as robust inference and the use of the bootstrap in a multivariate setting. A minimum background expected of the reader would include at least two courses in mathematical statistics, and certainly some exposure to the calculus of several variables together with the descriptive geometry of linear algebra.
Aspects Of Multivariate Statistical Theory
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Author : Robb J. Muirhead
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25
Aspects Of Multivariate Statistical Theory written by Robb J. Muirhead 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.
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. ". . . the wealth of material on statistics concerning the multivariate normal distribution is quite exceptional. As such it is a very useful source of information for the general statistician and a must for anyone wanting to penetrate deeper into the multivariate field." -Mededelingen van het Wiskundig Genootschap "This book is a comprehensive and clearly written text on multivariate analysis from a theoretical point of view." -The Statistician Aspects of Multivariate Statistical Theory presents a classical mathematical treatment of the techniques, distributions, and inferences based on multivariate normal distribution. Noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis are introduced. Advances in multivariate analysis are discussed, including decision theory and robustness. The book also includes tables of percentage points of many of the standard likelihood statistics used in multivariate statistical procedures. This definitive resource provides in-depth discussion of the multivariate field and serves admirably as both a textbook and reference.
The Theory Of Linear Models And Multivariate Analysis
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Author : Steven F. Arnold
language : en
Publisher: John Wiley & Sons
Release Date : 1981
The Theory Of Linear Models And Multivariate Analysis written by Steven F. Arnold 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 1981 with Mathematics categories.
Basic statistical definitions and theorems. Subspaces and projections. Properties of the multivariate and spherical normal distributions. Introduction to linear models. A sufficient statistic. Estimation. Tests about the mean. Simultaneous confidence intervals - scheffe type. Tests about the variance. Asymptotic validity of procedures under nonnormal distributions. James-Stein and Ridge estimators. Inference based on the studentized range distribution and bonferroni's inequality. The generalized linear model. The repeated measures model. Random effects and mixed models. The correlation model. The distribution theory for multivariate analysis. The multivariate one-and two-sample models - inference about the mean vector. The multivariate linear model. Discriminant analysis. Testing hypotheses about the covariance matrix. Simplifying the structure of the covariance matrix.
Discrete Multivariate Analysis
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Author : Yvonne M. Bishop
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-30
Discrete Multivariate Analysis written by Yvonne M. Bishop 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 2007-07-30 with Mathematics categories.
“A welcome addition to multivariate analysis. The discussion is lucid and very leisurely, excellently illustrated with applications drawn from a wide variety of fields. A good part of the book can be understood without very specialized statistical knowledge. It is a most welcome contribution to an interesting and lively subject.” -- Nature Originally published in 1974, this book is a reprint of a classic, still-valuable text.
Random Matrix Theory And Its Applications Multivariate Statistics And Wireless Communications
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Author : Zhidong Bai
language : en
Publisher: World Scientific
Release Date : 2009-07-27
Random Matrix Theory And Its Applications Multivariate Statistics And Wireless Communications written by Zhidong Bai and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-27 with Mathematics categories.
Random matrix theory has a long history, beginning in the first instance in multivariate statistics. It was used by Wigner to supply explanations for the important regularity features of the apparently random dispositions of the energy levels of heavy nuclei. The subject was further deeply developed under the important leadership of Dyson, Gaudin and Mehta, and other mathematical physicists.In the early 1990s, random matrix theory witnessed applications in string theory and deep connections with operator theory, and the integrable systems were established by Tracy and Widom. More recently, the subject has seen applications in such diverse areas as large dimensional data analysis and wireless communications.This volume contains chapters written by the leading participants in the field which will serve as a valuable introduction into this very exciting area of research.
Multiparametric Statistics
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Author : Vadim Ivanovich Serdobolskii
language : en
Publisher: Elsevier
Release Date : 2007-10-18
Multiparametric Statistics written by Vadim Ivanovich Serdobolskii and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-18 with Computers categories.
This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. Near exact solutions are constructed for a number of concrete multi-dimensional problems: estimation of expectation vectors, regression and discriminant analysis, and for the solution to large systems of empiric linear algebraic equations. It is remarkable that these solutions prove to be not only non-degenerating and always stable, but also near exact within a wide class of populations.In the conventional situation of small dimension and large sample size these new solutions far surpass the classical, commonly used consistent ones. It can be expected in the near future, for the most part, traditional multivariate statistical software will be replaced by the always reliable and more efficient versions of statistical procedures implemented by the technology described in this book.This monograph will be of interest to a variety of specialists working with the theory of statistical methods and its applications. Mathematicians would find new classes of urgent problems to be solved in their own regions. Specialists in applied statistics creating statistical packages will be interested in more efficient methods proposed in the book. Advantages of these methods are obvious: the user is liberated from the permanent uncertainty of possible instability and inefficiency and gets algorithms with unimprovable accuracy and guaranteed for a wide class of distributions.A large community of specialists applying statistical methods to real data will find a number of always stable highly accurate versions of algorithms that will help them to better solve their scientific or economic problems. Students and postgraduates will be interested in this book as it will help them get at the foremost frontier of modern statistical science. - Presents original mathematical investigations and open a new branch of mathematical statistics- Illustrates a technique for developing always stable and efficient versions of multivariate statistical analysis for large-dimensional problems - Describes the most popular methods some near exact solutions; including algorithms of non-degenerating large-dimensional discriminant and regression analysis
The Geometry Of Multivariate Statistics
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Author : Thomas D. Wickens
language : en
Publisher: Psychology Press
Release Date : 2014-02-25
The Geometry Of Multivariate Statistics written by Thomas D. Wickens and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-25 with Psychology categories.
A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.
Essays On The Theory Of Multivariate Statistics And Its Application To Problems In Business Research
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Author : Joseph F. Hair
language : en
Publisher:
Release Date : 1974
Essays On The Theory Of Multivariate Statistics And Its Application To Problems In Business Research written by Joseph F. Hair and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Economic research categories.
An Introduction To Multivariate Statistical Analysis
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Author : Theodore W. Anderson
language : en
Publisher:
Release Date : 1984-09-28
An Introduction To Multivariate Statistical Analysis written by Theodore W. Anderson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-09-28 with Mathematics categories.
1. Introduction; 2. The multivariate normal distribution; 3. Estimation of the mean vector and the covariance matrix; 4. Distributions and uses of sample correlation coefficients; 5. The generalized T2-Statistic; 6. Classification of observations; 7. The distribution of the sample covariance matrix and the sample generalized variance; 8. Testing the general linear hypothesis; Multivariate analysis of variance; 9. Testing independence of sets of variates; 10. Testing hypothesis of equality of coariance matrices and equality of mean vectors and covariance matrices; 11. Principal components; 12. Canonical correlations and canonical variables; 13. The distributions of characteristic roots and vectors; 14. Factor analysis.
Theory Of Multivariate Statistics
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Author : Martin Bilodeau
language : en
Publisher:
Release Date : 2014-01-15
Theory Of Multivariate Statistics written by Martin Bilodeau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.