Numerical Methods Of Statistics
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Numerical Methods of Statistics
Author: John F. Monahan
language: en
Publisher: Cambridge University Press
Release Date: 2011-04-18
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.
Numerical Analysis for Statisticians
Author: Kenneth Lange
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-05-17
Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.
Numerical Methods of Statistics
Author: John F. Monahan
language: en
Publisher: Cambridge University Press
Release Date: 2001-02-05
This 2001 book provides a basic background in numerical analysis and its applications in statistics.