pfvbm {BoltzMM} | R Documentation |
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.
pfvbm(xval, bvec, Mmat)
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. |
The probability of the random string xval
under a fully-visible Boltzmann machine with bias vector bvec
and interaction matrix Mmat
.
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.
# 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)