Computes the marginal probabilities (for values = +1 in each coordinate) under under some specified bias vector and interaction matrix, specified by
Vector of length n containing real valued bias parameters.
Symmetric n by n matrix, with zeros along the diagonal, containing the interaction parameters.
Vector of length n containing the marginal probabilities of +1 in each coordinate.
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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