BoltzMM (version 0.1.5)

marginpfvbm: Marginal probability function for a fully-visible Boltzmann machine.

Description

Computes the marginal probabilities (for values = +1 in each coordinate) under under some specified bias vector and interaction matrix, specified by bvec and Mmat, respectively.

Usage

marginpfvbm(bvec, Mmat)

Value

Vector of length n containing the marginal probabilities of +1 in each coordinate.

Arguments

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

#Compute the marginal probabilities under bvec and Mmat.
# Set the parameter values
bvec <- c(0,0.5,0.25)
Mmat <- matrix(0.1,3,3) - diag(0.1,3,3)
marginpfvbm(bvec,Mmat)