Multivariate Statistical Analysis in the Real and Complex Domains

Multivariate Statistical Analysis in the Real and Complex Domains
Author: Arak M. Mathai
Publisher: Springer Nature
Total Pages: 939
Release: 2022-10-04
Genre: Mathematics
ISBN: 3030958647

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.

Modern Multivariate Statistical Techniques

Modern Multivariate Statistical Techniques
Author: Alan J. Izenman
Publisher: Springer Science & Business Media
Total Pages: 757
Release: 2009-03-02
Genre: Mathematics
ISBN: 0387781897

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

Recent Trends in Fractional Calculus and Its Applications

Recent Trends in Fractional Calculus and Its Applications
Author: Praveen Agarwal
Publisher: Elsevier
Total Pages: 302
Release: 2024-07-02
Genre: Science
ISBN: 0443185069

Recent Trends in Fractional Calculus and Its Applications addresses the answer to this very basic question: "Why is Fractional Calculus important?" Until recent times, Fractional Calculus was considered as a rather esoteric mathematical theory without applications, but in the last few decades there has been an explosion of research activities on the application of Fractional Calculus to very diverse scientific fields ranging from the physics of diffusion and advection phenomena, to control systems to finance and economics. An important part of mathematical modelling of objects and processes is a description of their dynamics.The term Fractional Calculus is more than 300 years old. It is a generalization of the ordinary differentiation and integration to noninteger (arbitrary) order. The subject is as old as the calculus of differentiation and goes back to times when Leibniz, Gauss, and Newton invented this kind of calculation. Several mathematicians contributed to this subject over the years. People like Liouville, Riemann, and Weyl made major contributions to the theory of Fractional Calculus. In recent decades the field of Fractional Calculus has attracted the interest of researchers in several areas, including mathematics, physics, chemistry, engineering, finance, and social sciences. - Provides the most recent and up-to-date developments in the Fractional Calculus and its application areas - Presents pre-preparation ideas to help researchers/scientists/clinicians face the new challenges in the application of fractional differential equations - Helps researchers and scientists understand the importance of the Fractional Calculus to solve many problems in Biomedical Engineering and applied sciences

Statistical Factor Analysis and Related Methods

Statistical Factor Analysis and Related Methods
Author: Alexander T. Basilevsky
Publisher: John Wiley & Sons
Total Pages: 770
Release: 2009-09-25
Genre: Mathematics
ISBN: 0470317736

Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas: * The classical principal components model and sample-populationinference * Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain * Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores * The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable * Applications of factor models to the estimation of functionalforms and to least squares of regression estimators

An Introduction to Multivariate Statistical Analysis

An Introduction to Multivariate Statistical Analysis
Author: T. W. Anderson
Publisher: Wiley-Interscience
Total Pages: 721
Release: 2003-07-25
Genre: Business & Economics
ISBN: 9780471360919

Perfected over three editions and more than forty years, this field- and classroom-tested reference: * Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. * Treats all the basic and important topics in multivariate statistics. * Adds two new chapters, along with a number of new sections. * Provides the most methodical, up-to-date information on MV statistics available.

Special Functions: Fractional Calculus and the Pathway for Entropy

Special Functions: Fractional Calculus and the Pathway for Entropy
Author: Hans J. Haubold
Publisher: MDPI
Total Pages: 305
Release: 2018-03-23
Genre: Mathematics
ISBN: 3038426652

This book is a printed edition of the Special Issue "Special Functions: Fractional Calculus and the Pathway for Entropy Dedicated to Professor Dr. A.M. Mathai on the occasion of his 80th Birthday" that was published in Axioms

Making Sense of Multivariate Data Analysis

Making Sense of Multivariate Data Analysis
Author: John Spicer
Publisher: SAGE
Total Pages: 256
Release: 2005
Genre: Mathematics
ISBN: 9781412904018

A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.

Topological and Statistical Methods for Complex Data

Topological and Statistical Methods for Complex Data
Author: Janine Bennett
Publisher: Springer
Total Pages: 297
Release: 2014-11-19
Genre: Mathematics
ISBN: 3662449005

This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data. The book presents new methods that leverage the mutual strengths of both topological and statistical techniques to support the management, analysis, and visualization of complex data. It covers both theory and application and provides readers with an overview of important key concepts and the latest research trends. Coverage in the book includes multi-variate and/or high-dimensional analysis techniques, feature-based statistical methods, combinatorial algorithms, scalable statistics algorithms, scalar and vector field topology, and multi-scale representations. In addition, the book details algorithms that are broadly applicable and can be used by application scientists to glean insight from a wide range of complex data sets.