Description Usage Arguments Value Author(s) References Examples
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.
1 | marginpfvbm(bvec, Mmat)
|
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. |
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.
1 2 3 4 5 | #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)
|
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