Marginal probability function for a fully-visible Boltzmann machine.
Marginal probability function for a fully-visible Boltzmann machine.
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.
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.
Returns
Vector of length n containing the marginal probabilities of +1 in each coordinate.
Examples
#Compute the marginal probabilities under bvec and Mmat.# Set the parameter valuesbvec <- c(0,0.5,0.25)Mmat <- matrix(0.1,3,3)- diag(0.1,3,3)marginpfvbm(bvec,Mmat)
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.