| pfvbm {BoltzMM} | R Documentation |
Probability mass function of a fully-visible Boltzmann machine evaluated for an individual vector.
Description
Compute the probability of a string 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.
Usage
pfvbm(xval, bvec, Mmat)
Arguments
xval |
Vector of length n containing binary spin variables. |
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
The probability of the random string xval under a fully-visible Boltzmann machine with bias vector bvec and interaction matrix Mmat.
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 probability of the vector xval=(-1,1,-1), under bvec and Mmat.
xval <- c(-1,1,-1)
bvec <- c(0,0.5,0.25)
Mmat <- matrix(0.1,3,3) - diag(0.1,3,3)
pfvbm(xval,bvec,Mmat)