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Math Toolkit

John Maddock

Paul A. Bristow

Hubert Holin

Xiaogang Zhang

Bruno Lalande

Johan Råde

Gautam Sewani

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 the Library and its Examples and Tests
History and What's New
C99 and C++ TR1 C-style Functions
Contact Info and Support
Statistical Distributions and Functions
Statistical Distributions Tutorial
Overview of Distributions
Headers and Namespaces
Distributions are Objects
Generic operations common to all distributions are non-member functions
Complements are supported too - and when to use them
Parameters can be calculated
Summary
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
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
Gamma Functions
Gamma
Log Gamma
Digamma
Ratios of Gamma Functions
Incomplete Gamma Functions
Incomplete Gamma Function Inverses
Derivative of the Incomplete Gamma Function
Factorials and Binomial Coefficients
Factorial
Double Factorial
Rising Factorial
Falling Factorial
Binomial Coefficients
Beta Functions
Beta
Incomplete Beta Functions
The Incomplete Beta Function Inverses
Derivative of the Incomplete Beta Function
Error Functions
Error Functions
Error Function Inverses
Polynomials
Legendre (and Associated) Polynomials
Laguerre (and Associated) Polynomials
Hermite Polynomials
Spherical Harmonics
Bessel Functions
Bessel Function Overview
Bessel Functions of the First and Second Kinds
Modified Bessel Functions of the First and Second Kinds
Spherical Bessel Functions of the First and Second Kinds
Elliptic Integrals
Elliptic Integral Overview
Elliptic Integrals - Carlson Form
Elliptic Integrals of the First Kind - Legendre Form
Elliptic Integrals of the Second Kind - Legendre Form
Elliptic Integrals of the Third Kind - Legendre Form
Zeta Functions
Riemann Zeta Function
Exponential Integrals
Exponential Integral En
Exponential Integral Ei
Logs, Powers, Roots and Exponentials
log1p
expm1
cbrt
sqrt1pm1
powm1
hypot
Compile Time Power of a Runtime Base
Sinus Cardinal and Hyperbolic Sinus Cardinal Functions
Sinus Cardinal and Hyperbolic Sinus Cardinal Functions Overview
sinc_pi
sinhc_pi
Inverse Hyperbolic Functions
Inverse Hyperbolic Functions Overview
acosh
asinh
atanh
Floating Point Utilities
Rounding Truncation and Integer Conversion
Rounding Functions
Truncation Functions
Integer and Fractional Part Splitting (modf)
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
C99 and TR1 C Functions Overview
C99 C Functions
TR1 C Functions Quick Reference
Internal Details and Tools (Experimental)
Overview
Reused Utilities
Numeric Constants
Series Evaluation
Continued Fraction Evaluation
Polynomial and Rational Function Evaluation
Root Finding With Derivatives
Root Finding Without Derivatives
Locating Function Minima
Testing and Development
Polynomials
Minimax Approximations and the Remez Algorithm
Relative Error and Testing
Graphing, Profiling, and Generating Test Data for Special Functions
Use with User-Defined Floating-Point Types
Using With NTL - a High-Precision Floating-Point Library
Using With MPFR / GMP - a High-Precision Floating-Point Library
Conceptual Requirements for Real Number Types
Conceptual Requirements for Distribution Types
Conceptual Archetypes and Testing
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
Error Handling Policies
Internal Promotion Policies
Mathematically Undefined Function Policies
Discrete Quantile Policies
Precision Policies
Iteration Limits Policies
Using macros to Change the Policy Defaults
Setting Polices at Namespace Scope
Policy Class Reference
Performance
Performance Overview
Interpreting these Results
Getting the Best Performance from this Library
Comparing Compilers
Performance Tuning Macros
Comparisons to Other Open Source Libraries
The Performance Test Application
Backgrounders
Additional Implementation Notes
Relative Error
The Lanczos Approximation
The Remez Method
References
Library Status
History and What's New
Compilers
Known Issues, and Todo List
Credits and Acknowledgements

ISBN 0-9504833-2-X 978-0-9504833-2-0, Classification 519.2-dc22

This manual is also available in printer friendly PDF format.

Last revised: August 08, 2010 at 11:27:41 GMT


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