James E. Gentle's Books

Computational Statistics

By: James E. Gentle

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Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.

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732

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Springer Science & Business Media

Published Date

ISBN 10

0387981446

ISBN 13

9780387981444

Elements of Computational Statistics

By: James E. Gentle

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Elements of Computational Statistics

By: James E. Gentle

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

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427

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Springer Science & Business Media

Published Date

ISBN 10

0387216111

ISBN 13

9780387216119

Computational Statistics

By: James E. Gentle

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Computational Statistics

By: James E. Gentle

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732

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Springer Science & Business Media

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ISBN 10

0387981446

ISBN 13

9780387981444

Statistical Computing

By: WIlliam J. Kennedy,James E. Gentle

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Statistical Computing

By: WIlliam J. Kennedy,James E. Gentle

In this book the authors have assembled the "best techniques from a great variety of sources, establishing a benchmark for the field of statistical computing." ---Mathematics of Computation ." The text is highly readable and well illustrated with examples. The reader who intends to take a hand in designing his own regression and multivariate packages will find a storehouse of information and a valuable resource in the field of statistical computing.

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612

Publisher

Routledge

Published Date

ISBN 10

1351414585

ISBN 13

9781351414586

Matrix Algebra

Theory, Computations, and Applications in Statistics

By: James E. Gentle

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Matrix Algebra

Theory, Computations, and Applications in Statistics

By: James E. Gentle

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.

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Page Count

536

Publisher

Springer Science & Business Media

Published Date

ISBN 10

0387708731

ISBN 13

9780387708737

Random Number Generation and Monte Carlo Methods

By: James E. Gentle

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Random Number Generation and Monte Carlo Methods

By: James E. Gentle

Monte Carlo simulation has become one of the most important tools in all fields of science. This book surveys the basic techniques and principles of the subject, as well as general techniques useful in more complicated models and in novel settings. The emphasis throughout is on practical methods that work well in current computing environments.

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252

Publisher

Springer Science & Business Media

Published Date

ISBN 10

147572960X

ISBN 13

9781475729603

Numerical Linear Algebra for Applications in Statistics

By: James E. Gentle

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Numerical Linear Algebra for Applications in Statistics

By: James E. Gentle

Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern computer software for numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, factorisations, matrix and vector norms, and other topics in linear algebra. The book is essentially self- contained, with the topics addressed constituting the essential material for an introductory course in statistical computing. Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

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Page Count

229

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1461206235

ISBN 13

9781461206231

Statistical Analysis of Financial Data

With Examples In R

By: James Gentle

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Statistical Analysis of Financial Data

With Examples In R

By: James Gentle

Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to an appendix to the first chapter, where the basics of R, especially those most relevant in financial applications, are presented and illustrated. The appendix also describes how to use R to obtain current financial data from the internet. Chapter 2 describes the methods of exploratory data analysis, especially graphical methods, and illustrates them on real financial data. Chapter 3 covers probability distributions useful in financial analysis, especially heavy-tailed distributions, and describes methods of computer simulation of financial data. Chapter 4 covers basic methods of statistical inference, especially the use of linear models in analysis, and Chapter 5 describes methods of time series with special emphasis on models and methods applicable to analysis of financial data. Features * Covers statistical methods for analyzing models appropriate for financial data, especially models with outliers or heavy-tailed distributions. * Describes both the basics of R and advanced techniques useful in financial data analysis. * Driven by real, current financial data, not just stale data deposited on some static website. * Includes a large number of exercises, many requiring the use of open-source software to acquire real financial data from the internet and to analyze it.

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Page Count

666

Publisher

CRC Press

Published Date

ISBN 10

042993923X

ISBN 13

9780429939235

Book's by James E. Gentle

Computational Statistics

Computational Statistics

Elements of Computational Statistics

Elements of Computational Statistics

Computational Statistics

Computational Statistics

Statistical Computing

Statistical Computing

Matrix Algebra

Matrix Algebra

Random Number Generation and Monte Carlo Methods

Random Number Generation and Monte Carlo Methods

Numerical Linear Algebra for Applications in Statistics

Numerical Linear Algebra for Applications in Statistics

Statistical Analysis of Financial Data

Statistical Analysis of Financial Data

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