marginpfvbm function

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 values bvec <- 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.

Author(s)

Andrew T. Jones and Hien D. Nguyen

  • Maintainer: Andrew Thomas Jones
  • License: GPL-3
  • Last published: 2025-04-13

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