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18. Random Number Distributions

This chapter describes functions for generating random variates and computing their probability distributions. Samples from the distributions described in this chapter can be obtained using any of the random number generators in the library as an underlying source of randomness. In the simplest cases a non-uniform distribution can be obtained analytically from the uniform distribution of a random number generator by applying an appropriate transformation. This method uses one call to the random number generator.

More complicated distributions are created by the acceptance-rejection method, which compares the desired distribution against a distribution which is similar and known analytically. This usually requires several samples from the generator.

The functions described in this section are declared in `gsl_randist.h'.

18.1 The Gaussian Distribution  
18.2 The Gaussian Tail Distribution  
18.3 The Bivariate Gaussian Distribution  
18.4 The Exponential Distribution  
18.5 The Laplace Distribution  
18.6 The Exponential Power Distribution  
18.7 The Cauchy Distribution  
18.8 The Rayleigh Distribution  
18.9 The Rayleigh Tail Distribution  
18.10 The Landau Distribution  
18.11 The Levy alpha-Stable Distributions  
18.12 The Levy skew alpha-Stable Distribution  
18.13 The Gamma Distribution  
18.14 The Flat (Uniform) Distribution  
18.15 The Lognormal Distribution  
18.16 The Chi-squared Distribution  
18.17 The F-distribution  
18.18 The t-distribution  
18.19 The Beta Distribution  
18.20 The Logistic Distribution  
18.21 The Pareto Distribution  
18.22 The Spherical Distribution (2D & 3D)  
18.23 The Weibull Distribution  
18.24 The Type-1 Gumbel Distribution  
18.25 The Type-2 Gumbel Distribution  
18.26 General Discrete Distributions  
18.27 The Poisson Distribution  
18.28 The Bernoulli Distribution  
18.29 The Binomial Distribution  
18.30 The Negative Binomial Distribution  
18.31 The Pascal Distribution  
18.32 The Geometric Distribution  
18.33 The Hypergeometric Distribution  
18.34 The Logarithmic Distribution  
18.35 Shuffling and Sampling  
18.36 Examples  
18.37 References and Further Reading  


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This document was generated by Michael Stenner on February, 14 2002 using texi2html