marginpfvbm {BoltzMM}

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)

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.

Value

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

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

#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)