Title: Random Number Distributions

GSL::Rng#gaussian

GSL::Rng#gaussian(sigma)

These return a Gaussian random variate, with mean zero and standard deviation sigma. The argument sigma can be omitted in the case of unit Gaussian distribution, sigma=1.

GSL::Rng#gaussian_ratio_method

GSL::Rng#gaussian_ratio_method(sigma)

Use Kinderman-Monahan ratio method

GSL::Rng#gaussian_tail(a, sigma)

GSL::Rng#bivariate_gaussian(sigma_x, sigma_y, rho)

GSL::Rng#exponential(mu)

GSL::Rng#laplace(a)

GSL::Rng#exppow(a, b)

GSL::Rng#cauchy(a)

GSL::Rng#rayleigh(sigma)

GSL::Rng#rayleigh_tail(a, sigma)

GSL::Rng#landau()

GSL::Rng#levy(c, alpha)

GSL::Rng#levy_skew(c, alpha, beta)

GSL::Rng#gamma(a, b)

GSL::Rng#flat(a, b)

GSL::Rng#lognormal(zeta, sigma)

GSL::Rng#chisq(nu)

GSL::Rng#fdist(nu1, nu2)

GSL::Rng#tdist(nu)

GSL::Rng#beta(a, b)

GSL::Rng#logistic(a)

GSL::Rng#pareto(a, b)

...

and more, see the GSL reference.

GSL::Rng#shuffle(v, n)

This randomly shuffles the order of n objects, stored in the GSL::Vector object v.

GSL::Rng#choose(v, k)

This returns a GSL::Vector object with k objects taken randomly from the GSL::Vector object v.

The objects are sampled without replacement, thus each object can only appear once in the returned vector. It is required that k be less than or equal to the length of the vector v.

GSL::Rng#sample(v, k)

This method is like the method choose but samples k items from the original vector v with replacement, so the same object can appear more than once in the output sequence. There is no requirement that k be less than the length of v.

1 Module functions

GSL::Ran::gaussian_pdf(x, sigma)

This function computes the probability density at x for a Gaussian distribution with standard deviation sigma.

GSL::Ran::gaussian_tail_pdf(x, a, sigma)

GSL::Ran::bivariate_gaussian_pdf(x, y, sigma_x, sigma_y, rho)

GSL::Ran::exponential_pdf(x, mu)

GSL::Ran::laplace_pdf(x, a)

GSL::Ran::exppow_pdf(x, a, b)

GSL::Ran::cauchy_pdf(x, a)

GSL::Ran::rayleigh_pdf(x, sigma)

GSL::Ran::rayleigh_tail_pdf(x, a, sigma)

GSL::Ran::landau_pdf(x)

GSL::Ran::levy_pdf(x, c, alpha)

GSL::Ran::levy_skew_pdf(x, c, alpha, beta)

GSL::Ran::gamma_pdf(x, a, b)

GSL::Ran::flat_pdf(x, a, b)

GSL::Ran::lognormal_pdf(x, zeta, sigma)

GSL::Ran::chisq_pdf(x, nu)

GSL::Ran::fdist_pdf(x, nu1, nu2)

GSL::Ran::tdist_pdf(x, nu)

GSL::Ran::beta_pdf(x, a, b)

GSL::Ran::logistic_pdf(x, a)

GSL::Ran::pareto_pdf(x, a, b)

...

1.1 Cumulative Probabilities

These methods are defined as module functions of the modules GSL and GSL::Cdf, as

GSL::cdf_gaussian_P(x, sigma = 1)

GSL::Cdf::gaussian_P(x, sigma = 1)

GSL::cdf_gaussian_Q(x, sigma = 1)

GSL::Cdf::gaussian_Q(x, sigma = 1)

...

and more, see the GSL reference.

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