GSL::Rng#gaussian(sigma = 1)
GSL::Ran::gaussian(rng, sigma = 1)
GSL::Rng#ugaussian
GSL::Ran::ugaussian
GSL::Ran::gaussian_pdf(x, sigma = 1)
GSL::Rng#gaussian_ratio_method(sigma = 1)
GSL::Ran::gaussian_ratio_method(rng, sigma = 1)
GSL::Cdf::gaussian_P(x, sigma = 1)
GSL::Cdf::gaussian_Q(x, sigma = 1)
GSL::Cdf::gaussian_Pinv(P, sigma = 1)
GSL::Cdf::gaussian_Qinv(Q, sigma = 1)
GSL::Cdf::ugaussian_P(x)
GSL::Cdf::ugaussian_Q(x)
GSL::Cdf::ugaussian_Pinv(P)
GSL::Cdf::ugaussian_Qinv(Q)
GSL::Rng#gaussian_tail(a, sigma = 1)
GSL::Ran#gaussian_tail(rng, a, sigma = 1)
GSL::Rng#ugaussian_tail(a)
GSL::Ran#ugaussian_tail(rng)
GSL::Ran::gaussian_tail_pdf(x, a, sigma = 1)
GSL::Ran::ugaussian_tail_pdf(x, a)
GSL::Rng#bivariate_gaussian(sigma_x, sigma_y, rho)
GSL::Ran::bivariate_gaussian(rng, sigma_x, sigma_y, rho)
GSL::Ran::bivariate_gaussian_pdf(x, y, sigma_x, sigma_y, rho)
GSL::Rng#exponential(mu)
GSL::Ran::exponential(rng, mu)
GSL::Ran::exponential_pdf(x, mu)
GSL::Cdf::exponential_P(x, mu)
GSL::Cdf::exponential_Q(x, mu)
GSL::Cdf::exponential_Pinv(P, mu)
GSL::Cdf::exponential_Qinv(Q, mu)
GSL::Rng#laplace(a)
GSL::Ran::laplace(rng, a)
GSL::Ran::laplace_pdf(x, a)
GSL::Cdf::laplace_P(x, a)
GSL::Cdf::laplace_Q(x, a)
GSL::Cdf::laplace_Pinv(P, a)
GSL::Cdf::laplace_Qinv(Q, 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)
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)
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.