Elliptically Contoured Models In Statistics

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Elliptically Contoured Models in Statistics and Portfolio Theory

Author : Arjun K. Gupta
Publisher : Springer Science & Business Media
ISBN 13 : 1461481546
Total Pages : 332 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Elliptically Contoured Models in Statistics and Portfolio Theory by : Arjun K. Gupta

Download or read book Elliptically Contoured Models in Statistics and Portfolio Theory written by Arjun K. Gupta and published by Springer Science & Business Media. This book was released on 2013-09-07 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions. There are two additional chapters, and all the original chapters of this classic text have been updated. Resources in this book will be valuable for researchers, practitioners, and graduate students in statistics and related fields of finance and engineering. Those interested in multivariate statistical analysis and its application to portfolio theory will find this text immediately useful. In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Elliptical distributions have also increased their popularity in finance because of the ability to model heavy tails usually observed in real data. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. A noteworthy function of this book is the collection of the most important results on the theory of matrix variate elliptically contoured distributions that were previously only available in the journal-based literature. The content is organized in a unified manner that can serve an a valuable introduction to the subject.

Elliptically Contoured Models in Statistics

Author : Arjun K Gupta
Publisher :
ISBN 13 : 9789401116473
Total Pages : 340 pages
Book Rating : 4.1/5 (164 download)

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Book Synopsis Elliptically Contoured Models in Statistics by : Arjun K Gupta

Download or read book Elliptically Contoured Models in Statistics written by Arjun K Gupta and published by . This book was released on 1993-01-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Elliptically Contoured Models in Statistics

Author : Arjun K. Gupta
Publisher : Springer Science & Business Media
ISBN 13 : 9401116466
Total Pages : 336 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Elliptically Contoured Models in Statistics by : Arjun K. Gupta

Download or read book Elliptically Contoured Models in Statistics written by Arjun K. Gupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Modeling and Analysis for Complex Data Problems

Author : Pierre Duchesne
Publisher : Springer Science & Business Media
ISBN 13 : 0387245553
Total Pages : 330 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Statistical Modeling and Analysis for Complex Data Problems by : Pierre Duchesne

Download or read book Statistical Modeling and Analysis for Complex Data Problems written by Pierre Duchesne and published by Springer Science & Business Media. This book was released on 2005-12-05 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews some of today’s more complex problems, and reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

Credit Risk

Author : Georg Bol
Publisher : Springer Science & Business Media
ISBN 13 : 3642593658
Total Pages : 334 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Credit Risk by : Georg Bol

Download or read book Credit Risk written by Georg Bol and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: New developments in measuring, evaluating and managing credit risk are discussed in this volume. Addressing both practitioners in the banking sector and resesarch institutions, the book provides a manifold view on one of the most-discussed topics in finance. Among the subjects treated are important issues, such as: the consequences of the new Basel Capital Accord (Basel II), different applications of credit risk models, and new methodologies in rating and measuring credit portfolio risk. The volume provides an overview of recent developments as well as future trends: a state-of-the-art compendium in the area of credit risk.

Nonnormal Multivariate Distributions: Inference Based on Elliptically Contoured Distributions

Author : Stanford University. Department of Statistics
Publisher :
ISBN 13 :
Total Pages : 27 pages
Book Rating : 4.:/5 (333 download)

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Book Synopsis Nonnormal Multivariate Distributions: Inference Based on Elliptically Contoured Distributions by : Stanford University. Department of Statistics

Download or read book Nonnormal Multivariate Distributions: Inference Based on Elliptically Contoured Distributions written by Stanford University. Department of Statistics and published by . This book was released on 1992 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Model-Based Clustering and Classification for Data Science

Author : Charles Bouveyron
Publisher : Cambridge University Press
ISBN 13 : 110849420X
Total Pages : 446 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Model-Based Clustering and Classification for Data Science by : Charles Bouveyron

Download or read book Model-Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.

Growth Curve Models and Statistical Diagnostics

Author : Jian-Xin Pan
Publisher : Springer Science & Business Media
ISBN 13 : 0387218122
Total Pages : 406 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Growth Curve Models and Statistical Diagnostics by : Jian-Xin Pan

Download or read book Growth Curve Models and Statistical Diagnostics written by Jian-Xin Pan and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. Provided are complete proofs of theorems as well as practical data sets and MATLAB code.

Multidimensional Statistical Analysis and Theory of Random Matrices

Author : A. K. Gupta
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 311091669X
Total Pages : 400 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Multidimensional Statistical Analysis and Theory of Random Matrices by : A. K. Gupta

Download or read book Multidimensional Statistical Analysis and Theory of Random Matrices written by A. K. Gupta and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-01-14 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers from the Sixth Eugene Lukacs Symposium on ''Multidimensional Statistical Analysis and Random Matrices'', which was held at the Bowling Green State University, Ohio, USA, 29--30 March 1996. Multidimensional statistical analysis and random matrices have been the topics of great research. The papers presented in this volume discuss many varied aspects of this all-encompassing topic. In particular, topics covered include generalized statistical analysis, elliptically contoured distribution, covariance structure analysis, metric scaling, detection of outliers, density approximation, and circulant and band random matrices.

Linear Models in Statistics

Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Linear Models in Statistics by : Alvin C. Rencher

Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

Skew-Normal Model Theories and Their Applications

Author : Rendao Ye
Publisher : CRC Press
ISBN 13 : 1040155383
Total Pages : 273 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Skew-Normal Model Theories and Their Applications by : Rendao Ye

Download or read book Skew-Normal Model Theories and Their Applications written by Rendao Ye and published by CRC Press. This book was released on 2024-11-08 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest. This book is of academic value as it helps to establish a series of statistical inference theories and methods for skew-normal mixed effects models. On the applications side, it provides efficient methods and tools for practical data analysis in various fields including economics, finance, biology and medical science.

A First Course in Linear Model Theory

Author : Nalini Ravishanker
Publisher : CRC Press
ISBN 13 : 1351653199
Total Pages : 528 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis A First Course in Linear Model Theory by : Nalini Ravishanker

Download or read book A First Course in Linear Model Theory written by Nalini Ravishanker and published by CRC Press. This book was released on 2021-10-19 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the authors introduce to students the mathematical and statistical concepts and tools that form a foundation for studying the theory and applications of both univariate and multivariate linear models. In addition to adding R functionality, this second edition features three new chapters and several sections on new topics that are extremely relevant to the current research in statistical methodology. Revised or expanded topics include linear fixed, random and mixed effects models, generalized linear models, Bayesian and hierarchical linear models, model selection, multiple comparisons, and regularized and robust regression. New to the Second Edition: Coverage of inference for linear models has been expanded into two chapters. Expanded coverage of multiple comparisons, random and mixed effects models, model selection, and missing data. A new chapter on generalized linear models (Chapter 12). A new section on multivariate linear models in Chapter 13, and expanded coverage of the Bayesian linear models and longitudinal models. A new section on regularized regression in Chapter 14. Detailed data illustrations using R. The authors' fresh approach, methodical presentation, wealth of examples, use of R, and introduction to topics beyond the classical theory set this book apart from other texts on linear models. It forms a refreshing and invaluable first step in students' study of advanced linear models, generalized linear models, nonlinear models, and dynamic models.

Scientific Data Mining and Knowledge Discovery

Author : Mohamed Medhat Gaber
Publisher : Springer Science & Business Media
ISBN 13 : 3642027881
Total Pages : 398 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Scientific Data Mining and Knowledge Discovery by : Mohamed Medhat Gaber

Download or read book Scientific Data Mining and Knowledge Discovery written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2009-09-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mohamed Medhat Gaber “It is not my aim to surprise or shock you – but the simplest way I can summarise is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind has been applied” by Herbert A. Simon (1916-2001) 1Overview This book suits both graduate students and researchers with a focus on discovering knowledge from scienti c data. The use of computational power for data analysis and knowledge discovery in scienti c disciplines has found its roots with the re- lution of high-performance computing systems. Computational science in physics, chemistry, and biology represents the rst step towards automation of data analysis tasks. The rational behind the developmentof computationalscience in different - eas was automating mathematical operations performed in those areas. There was no attention paid to the scienti c discovery process. Automated Scienti c Disc- ery (ASD) [1–3] represents the second natural step. ASD attempted to automate the process of theory discovery supported by studies in philosophy of science and cognitive sciences. Although early research articles have shown great successes, the area has not evolved due to many reasons. The most important reason was the lack of interaction between scientists and the automating systems.

Matrix Variate Distributions

Author : A K Gupta
Publisher : CRC Press
ISBN 13 : 1351433008
Total Pages : 382 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Matrix Variate Distributions by : A K Gupta

Download or read book Matrix Variate Distributions written by A K Gupta and published by CRC Press. This book was released on 2018-05-02 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Analysis of Panel Data

Author : Cheng Hsiao
Publisher : Cambridge University Press
ISBN 13 : 1009076604
Total Pages : 539 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Analysis of Panel Data by : Cheng Hsiao

Download or read book Analysis of Panel Data written by Cheng Hsiao and published by Cambridge University Press. This book was released on 2022-07-07 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

Statistical Theory and Inference

Author : David J. Olive
Publisher : Springer
ISBN 13 : 3319049720
Total Pages : 438 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Statistical Theory and Inference by : David J. Olive

Download or read book Statistical Theory and Inference written by David J. Olive and published by Springer. This book was released on 2014-05-07 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.

Parametric Statistical Change Point Analysis

Author : Jie Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1475731310
Total Pages : 190 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Parametric Statistical Change Point Analysis by : Jie Chen

Download or read book Parametric Statistical Change Point Analysis written by Jie Chen and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently there has been a keen interest in the statistical analysis of change point detec tion and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, litera ture, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to de cide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the fol lowing period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regres sion and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential.