...one of the most highly
regarded and expertly designed C++ library projects in the
world.

— Herb Sutter and Andrei
Alexandrescu, C++
Coding Standards

Copyright © 2006 , 2007, 2008, 2009, 2010 John Maddock, Paul A. Bristow, Hubert Holin, Xiaogang Zhang, Bruno Lalande, Johan Råde, Gautam Sewani and Thijs van den Berg

Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

**Table of Contents**

- Overview
- About the Math Toolkit
- Navigation
- Directory and File Structure
- Namespaces
- Calculation of the Type of the Result
- Error Handling
- Compilers
- Configuration and Policies
- Thread Safety
- Performance
- If and How to Build a Boost.Math Library, and its Examples and Tests
- History and What's New
- C99 and C++ TR1 C-style Functions
- Frequently Asked Questions FAQ
- Contact Info and Support

- Statistical Distributions and Functions
- Statistical Distributions Tutorial
- Overview of Distributions
- Worked Examples
- Distribution Construction Example
- Student's t Distribution Examples
- Chi Squared Distribution Examples
- F Distribution Examples
- Binomial Distribution Examples
- Negative Binomial Distribution Examples
- Normal Distribution Examples
- Non Central Chi Squared Example
- Error Handling Example
- Find Location and Scale Examples
- Comparison with C, R, FORTRAN-style Free Functions
- Using the Distributions from Within C#

- Random Variates and Distribution Parameters
- Discrete Probability Distributions

- Statistical Distributions Reference
- Non-Member Properties
- Distributions
- Bernoulli Distribution
- Beta Distribution
- Binomial Distribution
- Cauchy-Lorentz Distribution
- Chi Squared Distribution
- Exponential Distribution
- Extreme Value Distribution
- F Distribution
- Gamma (and Erlang) Distribution
- Inverse Chi Squared Distribution
- Inverse Gamma Distribution
- Hypergeometric Distribution
- Laplace Distribution
- Logistic Distribution
- Log Normal Distribution
- Negative Binomial Distribution
- Noncentral Beta Distribution
- Noncentral Chi-Squared Distribution
- Noncentral F Distribution
- Noncentral T Distribution
- Normal (Gaussian) Distribution
- Pareto Distribution
- Poisson Distribution
- Rayleigh Distribution
- Students t Distribution
- Triangular Distribution
- Weibull Distribution
- Uniform Distribution

- Distribution Algorithms

- Extras/Future Directions

- Special Functions
- Floating Point Utilities
- Rounding Truncation and Integer Conversion
- Floating-Point Classification: Infinities and NaN's
- Sign Manipulation Functions
- Floating-Point Representation Distance (ULP), and Finding Adjacent Floating-Point Values
- Finding the Next Representable Value in a Specific Direction (nextafter)
- Finding the Next Greater Representable Value (float_next)
- Finding the Next Smaller Representable Value (float_prior)
- Calculating the Representation Distance Between Two Floating Point Values (ULP) float_distance
- Advancing a Floating Point Value by a Specific Representation Distance (ULP) float_advance

- TR1 and C99 external "C" Functions
- Internal Details and Tools (Experimental)
- Use with User-Defined Floating-Point Types
- Policies
- Policy Overview
- Policy Tutorial
- So Just What is a Policy Anyway?
- Policies Have Sensible Defaults
- So How are Policies Used Anyway?
- Changing the Policy Defaults
- Setting Policies for Distributions on an Ad Hoc Basis
- Changing the Policy on an Ad Hoc Basis for the Special Functions
- Setting Policies at Namespace or Translation Unit Scope
- Calling User Defined Error Handlers
- Understanding Quantiles of Discrete Distributions

- Policy Reference

- Performance
- Backgrounders
- Library Status

This manual is also available in printer friendly PDF format, and as a CD ISBN 0-9504833-2-X 978-0-9504833-2-0, Classification 519.2-dc22.

Last revised: October 25, 2010 at 16:12:20 GMT |