This module provides a set of predicates for sampling from various distributions. The state of the random generator is threaded through using the DCG idiom.

author

- Samer Abdallah

 bernoulli(+A:prob, -X:oneof([0,1]))// is det

Sample binary random variable.

 binomial(+P:float, +N:natural, -X:natural)// is det

Sample X from a binomial distribution, ie the number of successful trials out of N trials where the probability of success of each trial is P.

 poisson(+A:nonneg, -X:float)// is det

Sample from Poisson distribution of rate A.

 discrete(+A:list(prob), -X:natural)// is det

Sample from a discrete distribution over natural numbers.

 discrete(+O:list(T), +A:list(prob), -X:T)// is det

Sample from a discrete distribution over list of objects.

 uniform01(-X:float)// is det

Sample X from uniform distribution on [0,1).

 normal(-X:float)// is det

Sample from zero-mean unit-variance Gaussian.

 exponential(-X:float)// is det

Sample from unit-mean exponential distribution.

 stable(+A, +B, -X:float)// is det

Sample from a Levy-stable distribution.

 dirichlet(+A:list(nonneg), -X:list(prob))// is det

Sample from a Dirichlet distribution.

 uniform(+Items:list(A), -A)// is det

Uniform distribution over a finite number of items. uniform :: list(A) -> expr(A).

 uniformP(+P:dcg(-A), -A)// is det

Sample uniformly from all solutions to call(P,X).

 beta(+A:nonneg, +B:nonneg, -X:prob)// is det

Sample from beta distribution.

 zeta(+A:nonneg, -X:natural)// is det

Sample from zeta (hyperbolic or power law) distribution over natural numbers. NB: Must have A > 1.

 gamma(+A:nonneg, -X:float)// is det

Sample from gamma distribution with parameter A.

 gaussian(+Mean:float, +Var:nonneg, -X:float)// is det

gaussian :: \(float, nonneg) -> expr(float). Sample from Gaussian with given mean and variance.

 inv_gamma(+A:nonneg, -X:float)// is det

Sample from inverse gamma distribution with parameter A.

 students_t(+V:nonneg, -X:float)// is det

Sample from student's t distribution with V degrees of freedom.

 product_pair(+F:dist(A), +G:dist(B), -X:pair(A,B))// is det

Sample a pair from two independent distributions.

 mixture(+Sources:list(expr(A)), +Probs:list(prob), -X:A)// is det

Sample from discrete distribution over Sources with probabilities Probs and then sample from the resulting distribution.

mixture :: \(list(expr(A)), list(prob)) -> expr(A).

Undocumented predicates

The following predicates are exported, but not or incorrectly documented.

 uniformT(Arg1, Arg2, Arg3, Arg4)

 discreteT(Arg1, Arg2, Arg3, Arg4, Arg5)

 prob(Arg1, Arg2, Arg3)

 prob(Arg1, Arg2)

 pdf(Arg1, Arg2, Arg3)

 pdf(Arg1, Arg2)