Statistics, Data Processing, C/C++, Programming - General & Miscellaneous

C/C++ mathematical algorithms for scientists & engineers

Name: C/C++ mathematical algorithms for scientists & engineers
Author: Namir Clement Shammas
ISBN: 9780079120045

by Namir Clement Shammas

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Overview

Analyze complex numerical data and get the answers you need fast with this time-saving toolbox of powerful C and C++ mathematical routines. All of the programs are written in C, with C++ extensions provided for those cases where using the C++ classes offers a special advantage. The code is compatible with a variety of platforms, including UNIX, Windows, and DOS. Author and programming expert Namir Shammas covers a wide range of popular numerical analysis and statistical topics: solving linear and nonlinear equations; interpolation use methods; differentiation - tools for estimating the derivative of a function; integration - tools for calculating the finite and infinite integrals for functions; optimization of single-variable and multivariable functions; basic statistics; various types of ANOVA tables; linear regression; and multiple and polynomial regression. In addition to providing libraries for common mathematical and statistical functions, Shammas includes pseudo-code for the algorithms used to implement the various methods, allowing you to execute these algorithms in other programming languages, such as BASIC and Pascal.

A valuable book/disk set offering scientists, engineers, statisticians, and programmers a toolbox of essential numerical routines in C and C++. The programs are all be written in C, with C++ extensions provided where the object-oriented language provides a benefit. Providing the routines in both C and C++ helps scientists and engineers familiar with C to learn C++.

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Provides mathematical routines for analyzing complex numerical data, offering code written in C, with C++ extensions, for solving linear and nonlinear equations; interpolation; differentiation; integration; optimization of single variable and multivariable functions; linear regressions; and multiple and polynomial regression. Includes libraries for common mathematical and statistical functions, pseudo- code for the algorithms used to implement the various methods, and information on basic statistics and ANOVA tests. Annotation c. Book News, Inc., Portland, OR (booknews.com)