rfvbm: Random data generation from a fully-visible Boltzmann...

In BoltzMM: Boltzmann Machines with MM Algorithms

Random data generation from a fully-visible Boltzmann machine.

Description

Generate N random strings of n>1 binary spin variables (i.e. each element is -1 or 1) arising from a fully-visible Boltzmann machine with some specified bias vector and interaction matrix.

Usage

rfvbm(num, bvec, Mmat)

Arguments

num	Number N of random strings to be generated.
bvec	Vector of length n containing real valued bias parameters.
Mmat	Symmetric n by n matrix, with zeros along the diagonal, containing the interaction parameters.

Value

An N by n matrix, where each row contains a random spin variable string from a fully-visible Boltzmann machine with bias vector bvec and interaction matrix Mmat.

Note

The function allpfvbm must be called each time this function is run. Thus, it is much more efficient to generate N strings all at once, than to generate strings one at a time.

Author(s)

Andrew T. Jones and Hien D. Nguyen

References

H.D. Nguyen and I.A. Wood (2016), Asymptotic normality of the maximum pseudolikelihood estimator for fully-visible Boltzmann machines, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, pp. 897-902.

Examples

# Generate num=10 random strings of n=3 binary spin variables under bvec and Mmat.
num <- 10
bvec <- c(0,0.5,0.25)
Mmat <- matrix(0.1,3,3) - diag(0.1,3,3)
rfvbm(num,bvec,Mmat)

BoltzMM documentation built on April 13, 2025, 5:09 p.m.