Description Usage Arguments Details Value Note Author(s) References See Also Examples
Posterior probability calculation. Usually called internally.
1 2 3 4 |
phi |
The candidate network. |
L |
The likelihood computed by |
lambda |
Laplace prior hyperparameter describing the prior influence strength. |
B |
Laplace prior probability matrix. |
Z |
Laplace prior normalisation factor for the prior. (Not used at the moment.) |
gam |
Scale-free prior degree distribution coefficient: P(k) ~ k^gam |
N |
Number of nodes |
K |
Scale-free prior scaling factor/Strength |
it |
Scale-free prior number of iterations for prior sampling. |
priortype |
Character. One of |
Computes the posterior density depending on priortype
: uniform
uses uniform prior, laplaceinhib
and laplace
use
prior parameters lambda, gam, B and Z, and scalefree
uses gam and K as prior parameters. See prior
for a description of
the prior models.
A double containing the posterior density.
TODO
Christian Bender
Laplace prior
Froehlich et. al. 2007, Large scale statistical inference of signaling pathways from RNAi
and microarray data.
Scale free prior
Kamimura and Shimodaira, A Scale-free Prior over Graph Structures for Bayesian Inference of Gene Networks
TODO
1 | ## TODO
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