Compute the probability of all 2^n 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.
Vector of length n containing real valued bias parameters.
Symmetric n by n matrix, with zeros along the diagonal, containing the interaction parameters.
A vector of the probabilities of all 2^n binary spin vectors under a fully-visible Boltzmann machine with bias vector
bvec and interaction matrix
Mmat. Probabilities are reported in ascending order of the binary strings; i.e for n=2 the reporting order is (-1,1), (-1,1), (1,-1), and (1,1).
Andrew T. Jones and Hien D. Nguyen
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.
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