A Handbook of Numerical and Statistical Techniques

A Handbook of Numerical and Statistical Techniques
Author: J. H. Pollard
Publisher: CUP Archive
Total Pages: 372
Release: 1977
Genre: Mathematics
ISBN: 9780521297509

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This handbook is designed for experimental scientists, particularly those in the life sciences. It is for the non-specialist, and although it assumes only a little knowledge of statistics and mathematics, those with a deeper understanding will also find it useful. The book is directed at the scientist who wishes to solve his numerical and statistical problems on a programmable calculator, mini-computer or interactive terminal. The volume is also useful for the user of full-scale computer systems in that it describes how the large computer solves numerical and statistical problems. The book is divided into three parts. Part I deals with numerical techniques and Part II with statistical techniques. Part III is devoted to the method of least squares which can be regarded as both a statistical and numerical method. The handbook shows clearly how each calculation is performed. Each technique is illustrated by at least one example and there are worked examples and exercises throughout the volume.

Computational Methods for Numerical Analysis with R

Computational Methods for Numerical Analysis with R
Author: James P Howard, II
Publisher: CRC Press
Total Pages: 257
Release: 2017-07-12
Genre: Mathematics
ISBN: 1498723640

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Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.

Programming in C and Numerical Analysis

Programming in C and Numerical Analysis
Author: J.B. Dixit
Publisher: Firewall Media
Total Pages: 686
Release: 2006
Genre: C (Computer program language)
ISBN: 9788170088875

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C Programming

C Programming
Author: Madhumangal Pal
Publisher: Alpha Science International, Limited
Total Pages: 0
Release: 2013
Genre: Computers
ISBN: 9781842657584

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Includes exercises at the end of chapters to help develop C programming skills.

An Introduction to Numerical Methods in C++

An Introduction to Numerical Methods in C++
Author: Brian Hilton Flowers
Publisher:
Total Pages: 616
Release: 2000
Genre: Computers
ISBN: 9780198506935

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Designed for the many applied mathematicians and engineers who wish to explore computerized numerical methods, this text explores the power of C++ as a tool for work in numerical methods. This revision of the successful first edition includes for the first time information on programming in Windows-based environments. In addition it includes new topics and methods throughout the text that clarify and enhance the treatment of the subject.

Numerical Methods in Finance with C++

Numerical Methods in Finance with C++
Author: Maciej J. Capiński
Publisher: Cambridge University Press
Total Pages: 177
Release: 2012-08-02
Genre: Business & Economics
ISBN: 0521177162

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This book provides aspiring quant developers with the numerical techniques and programming skills needed in quantitative finance. No programming background required.

Numerical Methods of Statistics

Numerical Methods of Statistics
Author: John F. Monahan
Publisher: Cambridge University Press
Total Pages: 465
Release: 2011-04-18
Genre: Computers
ISBN: 1139498002

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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 Techniques

Numerical Techniques
Author: Dr. J. S. Chitode
Publisher: Technical Publications
Total Pages: 638
Release: 2021-01-01
Genre: Technology & Engineering
ISBN: 9333224033

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The book comprises of various numerical methods and their implementation with C-language and MATLAB. Basics of C-programming are covered in first chapter. Basics of errors in computation, number representation and its impact on errors is covered in second chapter. Various types of errors, their propagation, analysis and estimation is also covered in this chapter. Roots of transcendental equations are covered in third chapter. Birge-vieta method, Bairstow method, Bisection method, Secant method, Regula Falsi, Newton Raphson methods are discussed in detail. Fourth chapter focuses mainly on solution of simultaneous linear equations. Graphical, matrix inversion, substitution, Gauss' elimination, Gauss Jordan, LU decomposition, Gauss Seidel methods are discussed with the help of numerical examples. Curve fitting is discussed in fifth chapter. Finite differences operators, finite differences, Newton's forward and backward difference interpolation, divided differences interpolation, Lagrange’s interpolation, inverse interpolation, least squares approximation are presented. Numerical differentiation and integration is given in sixth and seventh chapter. Simpson's and trapezoidal rules of integration are presented. Solution of ordinary differential equations is given in eighth chapter. Taylor series, Picard’s methods, Euler's RK methods, Predictor corrector methods, boundary value problems and eigen value problems are also presented. Last chapter deals with unconstrained and constrained optimization. All the methods are implemented using C-program and some of them with MATLAB. Large number of solved and unsolved examples are also given.