BoltzMM (version 0.1.5)

rfvbm: 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)

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.

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.

Author

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)