The Geometry of Multivariate Statistics

Author: Thomas D. Wickens

Publisher: Psychology Press

ISBN: 131778023X

Category: Psychology

Page: 176

View: 2123

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.

Theory of Multivariate Statistics

Author: Martin Bilodeau,David Brenner

Publisher: Springer Science & Business Media

ISBN: 0387226168

Category: Mathematics

Page: 290

View: 5188

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.

Lineare Algebra

Author: Gilbert Strang

Publisher: Springer-Verlag

ISBN: 3642556310

Category: Mathematics

Page: 656

View: 3221

Diese Einführung in die lineare Algebra bietet einen sehr anschaulichen Zugang zum Thema. Die englische Originalausgabe wurde rasch zum Standardwerk in den Anfängerkursen des Massachusetts Institute of Technology sowie in vielen anderen nordamerikanischen Universitäten. Auch hierzulande ist dieses Buch als Grundstudiumsvorlesung für alle Studenten hervorragend lesbar. Darüber hinaus gibt es neue Impulse in der Mathematikausbildung und folgt dem Trend hin zu Anwendungen und Interdisziplinarität. Inhaltlich umfasst das Werk die Grundkenntnisse und die wichtigsten Anwendungen der linearen Algebra und eignet sich hervorragend für Studierende der Ingenieurwissenschaften, Naturwissenschaften, Mathematik und Informatik, die einen modernen Zugang zum Einsatz der linearen Algebra suchen. Ganz klar liegt hierbei der Schwerpunkt auf den Anwendungen, ohne dabei die mathematische Strenge zu vernachlässigen. Im Buch wird die jeweils zugrundeliegende Theorie mit zahlreichen Beispielen aus der Elektrotechnik, der Informatik, der Physik, Biologie und den Wirtschaftswissenschaften direkt verknüpft. Zahlreiche Aufgaben mit Lösungen runden das Werk ab.

Differentialgeometrie von Kurven und Flächen

Author: Manfredo P. do Carmo

Publisher: Springer-Verlag

ISBN: 3322850722

Category: Technology & Engineering

Page: 263

View: 8641

Inhalt: Kurven - Reguläre Flächen - Die Geometrie der Gauß-Abbildung - Die innere Geometrie von Flächen - Anhang

Data Depth

Robust Multivariate Analysis, Computational Geometry, and Applications

Author: Regina Y. Liu,Robert Joseph Serfling,Diane L. Souvaine

Publisher: American Mathematical Soc.

ISBN: 9780821871126

Category: Mathematics

Page: 246

View: 8341

The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University. The workshop brought together researchers from two different communities: statisticians and specialists in computational geometry. The main idea unifying these two research areas turned out to be the notion of data depth, which is an important notion both in statistics and in the study of efficiency of algorithms used in computational geometry. Many ofthe articles in the book lay down the foundations for further collaboration and interdisciplinary research. Information for our distributors: Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with theAssociation for Computer Machinery (ACM).

Mathematical Tools for Applied Multivariate Analysis

Author: Paul E. Green

Publisher: Academic Press

ISBN: 1483214044

Category: Mathematics

Page: 402

View: 2066

Mathematical Tools for Applied Multivariate Analysis provides information pertinent to the aspects of transformational geometry, matrix algebra, and the calculus that are most relevant for the study of multivariate analysis. This book discusses the mathematical foundations of applied multivariate analysis. Organized into six chapters, this book begins with an overview of the three problems in multiple regression, principal components analysis, and multiple discriminant analysis. This text then presents a standard treatment of the mechanics of matrix algebra, including definitions and operations on matrices, vectors, and determinants. Other chapters consider the topics of eigenstructures and linear transformations that are important to the understanding of multivariate techniques. This book discusses as well the eigenstructures and quadratic forms. The final chapter deals with the geometric aspects of linear transformations. This book is a valuable resource for students.

Geometric Morphometrics for Biologists

A Primer

Author: Miriam Leah Zelditch,Donald L. Swiderski,H. David Sheets

Publisher: Academic Press

ISBN: 0123869048

Category: Mathematics

Page: 488

View: 9491

The first edition of Geometric Morphometrics for Biologists has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses. Contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensics Offers a reorganization of chapters to streamline learning basic concepts Presents detailed instructions for conducting analyses with freely available, easy to use software Provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results

Wahrscheinlichkeitstheorie und Stochastische Prozesse

Author: Michael Mürmann

Publisher: Springer-Verlag

ISBN: 364238160X

Category: Mathematics

Page: 428

View: 2366

Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

Computational Social Network Analysis

Trends, Tools and Research Advances

Author: Kai Subel,Michel Schultz

Publisher: GRIN Verlag

ISBN: 3640733061

Category: Computers

Page: 21

View: 4270

Studienarbeit aus dem Jahr 2010 im Fachbereich Informatik - Internet, neue Technologien, Universität Hamburg, Sprache: Deutsch, Abstract: Diese Ausarbeitung befasst sich mit dem Thema Computational Soical Network Analysis. Ziel ist es, dem Leser einen Einblick in diese Thematik zu verschaffen. Dabei werden Hintergründe, anwendbare Methoden und Tools vorgestellt, die hierbei Verwendung finden. Zunächst wird dabei näher auf den Hintergrund, also warum dieses Gebiet als Forschungsgegenstand so interessant ist, eingegangen. Anschließend werden verschiedene Aspekte, die man im Rahmen der Analyse sozialer Netzwerke untersuchen kann benannt. In diesem Zusammenhang werden auch zwei verschiedene Kategorien zur formalen Analyse benannt. Zur Verdeutlichung wird die Verwendung dieser am Ende des Kapitels auch noch einmal anhand eines Praxisbeispiels gezeigt. Das nächste Kapitel befasst sich mit der Fragstellung, wie Schlüsselfiguren in Netzwerken ermittelt werden können und was für Rollen diese spielen. Dabei werden auch die verschiedenen Arten von Schlüsselfiguren benannt. Eine weitere zentrale Rolle in der Analyse sozialer Netzwerke nehmen Gruppen ein. Die Bedeutung von Gruppen und wie man sie ermitteln kann wird im nächsten Kapitel erläutert. Aufbauend auf den Gruppen sollen Interaktionen innerhalb von Netzwerken untersucht werden. Hierfür werden zunächst die nötigen Werkzeuge, wie die SCAN oder DISSECT Methode vorgestellt und anschließend die Einsatzgebiete anhand von Beispielen verdeutlicht. Im 7. Kapitel wird eine eLearning Plattform näher betrachtet. Hierbei werden zunächst die Eigenschaften und Besonderheiten von eLearning Plattformen beschrieben und anschießend anhand eines Praxisbeispiels verschiedene Methoden zur Analyse sozialer Netzwerke angewendet.

The Geometry of Urban Layouts

A Global Comparative Study

Author: Mahbub Rashid

Publisher: Springer

ISBN: 3319307509

Category: Political Science

Page: 453

View: 6484

This book presents a compendium of the urban layout maps of 2-mile square downtown areas of more than one hundred cities in developed and developing countries—all drawn at the same scale using high-resolution satellite images of Google Maps. The book also presents analytic studies using metric geometrical, topological (or network), and fractal measures of these maps. These analytic studies identify ordinaries, extremes, similarities, and differences in these maps; investigate the scaling properties of these maps; and develop precise descriptive categories, types and indicators for multidimensional comparative studies of these maps. The findings of these studies indicate that many geometric relations of the urban layouts of downtown areas follow regular patterns; that despite social, economic, and cultural differences among cities, the geometric measures of downtown areas in cities of developed and developing countries do not show significant differences; and that the geometric possibilities of urban layouts are vastly greater than those that have been realized so far in our cities.

Modern Multivariate Statistical Techniques

Regression, Classification, and Manifold Learning

Author: Alan J. Izenman

Publisher: Springer Science & Business Media

ISBN: 9780387781891

Category: Mathematics

Page: 733

View: 4029

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.

Statistics for the 21st Century

Methodologies for Applications of the Future

Author: Gabor Szekely

Publisher: CRC Press

ISBN: 9780824790295

Category: Mathematics

Page: 500

View: 9355

A selection of articles presented at the Eighth Lukacs Symposium held at the Bowling Green State University, Ohio. They discuss consistency and accuracy of the sequential bootstrap, hypothesis testing, geometry in multivariate analysis, the classical extreme value model, the analysis of cross-classified data, diffusion models for neural activity, estimation with quadratic loss, econometrics, higher order asymptotics, pre- and post-limit theorems, and more.

A Course in the Geometry of N Dimensions

Author: Maurice G. Kendall

Publisher: Courier Corporation

ISBN: 0486439275

Category: Mathematics

Page: 63

View: 8790

This text for undergraduate students provides a foundation for resolving proofs dependent on n-dimensional systems. The two-part treatment begins with simple figures in n dimensions and advances to examinations of the contents of hyperspheres, hyperellipsoids, hyperprisms, etc. The second part explores the mean in rectangular variation, the correlation coefficient in bivariate normal variation, Wishart's distribution, more. 1961 edition.

Multivariate Analysis: Future Directions 2

Author: C.M. Cuadras,C.R. Rao

Publisher: Elsevier

ISBN: 148329756X

Category: Mathematics

Page: 494

View: 4904

The contributions in this volume, made by distinguished statisticians in several frontier areas of research in multivariate analysis, cover a broad field and indicate future directions of research. The topics covered include discriminant analysis, multidimensional scaling, categorical data analysis, correspondence analysis and biplots, association analysis, latent variable models, bootstrap distributions, differential geometry applications and others. Most of the papers propose generalizations or new applications of multivariate analysis. This volume will be of great interest to statisticians, probabilists, data analysts and scientists working in the disciplines such as biology, biometry, ecology, medicine, econometry, psychometry and marketing. It will be a valuable guide to professors, researchers and graduate students seeking new and promising lines of statistical research.

Geometric Data Analysis

From Correspondence Analysis to Structured Data Analysis

Author: Brigitte Le Roux,Henry Rouanet

Publisher: Springer Science & Business Media

ISBN: 9781402022364

Category: Mathematics

Page: 475

View: 3001

Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis.

Discrete Multivariate Analysis

Theory and Practice

Author: Yvonne M. Bishop,Stephen E. Fienberg,Paul W. Holland

Publisher: Springer Science & Business Media

ISBN: 0387728066

Category: Mathematics

Page: 559

View: 6203

“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.

Mathematische Modellierung

Author: Christof Eck,Harald Garcke,Peter Knabner

Publisher: Springer-Verlag

ISBN: 3662543354

Category: Mathematics

Page: 515

View: 8442

Das Lehrbuch bietet eine lebendige und anschauliche Einführung in die mathematische Modellierung von Phänomenen aus den Natur- und Ingenieurwissenschaften. Leser lernen, mathematische Modelle zu verstehen und selbst herzuleiten und finden eine Fülle von Beispielen, u. a. aus den Bereichen chemische Reaktionskinetik, Populationsdynamik, Strömungsdynamik, Elastizitätstheorie und Kristallwachstum. Die Methoden der Linearen Algebra, der Analysis und der Theorie der gewöhnlichen und partiellen Differentialgleichungen werden sorgfältig eingeführt.

Einführung in die Komplexe Analysis

Elemente der Funktionentheorie

Author: Wolfgang Fischer,Ingo Lieb

Publisher: Springer-Verlag

ISBN: 3834893773

Category: Mathematics

Page: 214

View: 6850

In den Bachelor-Studiengängen der Mathematik steht für die Komplexe Analysis (Funktionentheorie) oft nur eine einsemestrige 2-stündige Vorlesung zur Verfügung. Dieses Buch eignet sich als Grundlage für eine solche Vorlesung im 2. Studienjahr. Mit einer guten thematischen Auswahl, vielen Beispielen und ausführlichen Erläuterungen gibt dieses Buch eine Darstellung der Komplexen Analysis, die genau die Grundlagen und den wesentlichen Kernbestand dieses Gebietes enthält. Das Buch bietet über diese Grundausbildung hinaus weiteres Lehrmaterial als Ergänzung, sodass es auch für eine 3- oder 4 –stündige Vorlesung geeignet ist. Je nach Hörerkreis kann der Stoff unterschiedlich erweitert werden. So wurden für den „Bachelor Lehramt“ die geometrischen Aspekte der Komplexen Analysis besonders herausgearbeitet.

Multivariate statistics

a vector space approach

Author: Morris L. Eaton

Publisher: Inst of Mathematical Statistic

ISBN: 9780940600690

Category: Mathematics

Page: 512

View: 6729

Building from his lecture notes, Eaton (mathematics, U. of Minnesota) has designed this text to support either a one-year class in graduate-level multivariate courses or independent study. He presents a version of multivariate statistical theory in which vector space and invariance methods replace to a large extent more traditional multivariate methods. Using extensive examples and exercises Eaton describes vector space theory, random vectors, the normal distribution on a vector space, linear statistical models, matrix factorization and Jacobians, topological groups and invariant measures, first applications of invariance, the Wishart distribution, inferences for means in multivariate linear models and canonical correlation coefficients. Eaton also provides comments on selected exercises and a bibliography.