Numerical methods of statistics / John F. Monahan.

Format:

Book

Author/Creator:

Monahan, John F., author.

Series:

Cambridge series on statistical and probabilistic mathematics.

Cambridge series on statistical and probabilistic mathematics

Language:

English

Subjects (All):

Mathematical statistics--Data processing.

Mathematical statistics.

Numerical analysis.

Physical Description:

1 online resource (xvi, 447 pages) : digital, PDF file(s).

Edition:

Second edition.

Place of Publication:

Cambridge : Cambridge University Press, 2011.

Language Note:

English

Summary:

This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available from the author's website. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder-Mead search algorithm.

Contents:

Cover; Half-title; Series-title; Title; Copyright; Contents; Preface to the Second Edition; Preface to the First Edition; 1 Algorithms and Computers; 2 Computer Arithmetic; 3 Matrices and Linear Equations; 4 More Methods for Solving Linear Equations; 5 Regression Computations; 6 Eigenproblems; 7 Functions: Interpolation, Smoothing, and Approximation; 8 Introduction to Optimization and Nonlinear Equations; 9 Maximum Likelihood and Nonlinear Regression; 10 Numerical Integration and Monte Carlo Methods; 11 Generating Random Variables from Other Distributions

12 Statistical Methods for Integration and Monte Carlo13 Markov Chain Monte Carlo Methods; 14 Sorting and Fast Algorithms; Author Index; Subject Index

Notes:

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Includes bibliographical references and indexes.

ISBN:

1-107-21389-4

1-283-11232-9

9786613112323

1-139-07529-2

1-139-07755-4

1-139-06952-7

1-139-07984-0

0-511-97717-4

1-139-08211-6

OCLC:

726734764