Patent Document ID: 7937339
Application ID: 12442456
Patent Flag: 1

Claim One:
1. A computer-implemented Markov Chain Monte Carlo method of sampling for purposes of generating a sequence of instances of a Bayesian network such that a distribution of values across the sequence of instances follows the same distribution as the actual probability density function for at least one variable comprising: (a) selecting by a computer a function, g(X), that is directly proportional to a probability density function, f, where f provides a probability distribution of a particular value of a variable, X, in a Bayesian network; (b) selecting by a computer a first sample value of X uniformly distributed over the domain of X; (c) picking by a computer a random value, y, between 0 and the value of g(X) for the first value of X; (d) choosing by a computer another value of X uniformly distributed over the whole domain of X; (e) if the value g(X) for the another value of X is less than the random value, y, discarding the second value, X i , and iterating (d), (e), and (f); and (f) if the value g(X) for the another value of X is greater than the random value, y, using the another value of X as a sample to generate a next instance of the Bayesian network.