allpfvbm: Probability mass function of a fully-visible Boltzmann...

Description Usage Arguments Value Author(s) References Examples

Description

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.

Usage

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allpfvbm(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.

Value

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).

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

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# Compute the probability of every length n=3 binary spin vector under bvec and Mmat.
bvec <- c(0,0.5,0.25)
Mmat <- matrix(0.1,3,3) - diag(0.1,3,3)
allpfvbm(bvec,Mmat)

BoltzMM documentation built on May 2, 2019, 11:02 a.m.