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

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

Copyright © 2006-2010, 2012 John Maddock, Paul A. Bristow, Hubert Holin, Xiaogang Zhang, Bruno Lalande, Johan Råde, Gautam Sewani, Thijs van den Berg and Benjamin Sobotta

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
- Document Conventions
- Other Hints and tips
- Directory and File Structure
- Namespaces
- Calculation of the Type of the Result
- Error Handling
- Compilers
- Configuration Macros
- 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
- Geometric Distribution Examples
- Negative Binomial Distribution Examples
- Normal Distribution Examples
- Inverse Chi-Squared Distribution Bayes Example
- 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
- Geometric Distribution
- Hypergeometric Distribution
- Inverse Chi Squared Distribution
- Inverse Gamma Distribution
- Inverse Gaussian (or Inverse Normal) 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
- Skew Normal Distribution
- Students t Distribution
- Triangular Distribution
- Uniform Distribution
- Weibull Distribution

- Distribution Algorithms

- Extras/Future Directions

- Special Functions
- Gamma Functions
- Factorials and Binomial Coefficients
- Beta Functions
- Error Functions
- Polynomials
- Bessel Functions
- Hankel Functions
- Airy Functions
- Elliptic Integrals
- Jacobi Elliptic Functions
- Overvew of the Jacobi Elliptic Functions
- Jacobi Elliptic SN, CN and DN
- Jacobi Elliptic Function cd
- Jacobi Elliptic Function cn
- Jacobi Elliptic Function cs
- Jacobi Elliptic Function dc
- Jacobi Elliptic Function dn
- Jacobi Elliptic Function ds
- Jacobi Elliptic Function nc
- Jacobi Elliptic Function nd
- Jacobi Elliptic Function ns
- Jacobi Elliptic Function sc
- Jacobi Elliptic Function sd
- Jacobi Elliptic Function sn

- Zeta Functions
- Exponential Integrals
- Logs, Powers, Roots and Exponentials
- Sinus Cardinal and Hyperbolic Sinus Cardinal Functions
- Inverse Hyperbolic Functions
- Owen's T function

- Floating Point Utilities
- Rounding Truncation and Integer Conversion
- Floating-Point Classification: Infinities and NaNs
- Sign Manipulation Functions
- Facets for Floating-Point Infinities and NaNs
- 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
- Mathematical Constants
- Tools and Internal Details
- 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
- Function Index
- Class Index
- Typedef Index
- Macro Index
- Index

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: January 21, 2013 at 11:50:21 GMT |