plot.bnpostmcmc: Plot top graphs.
In rjbgoudie/structmcmc: Structural inference for Bayesian Networks and Variable Selection.
Description
Usage
Arguments
Value
See Also
Description
Plot the the top() Bayesian Networks from a posterior
distribution. The top graphs are those with the highest
score with respect to the posterior distribution, which
for converged MCMC will be most commonly encountered
graph.
Usage
1
2
Arguments
x
An object of class "bnpostmcmc" or "bnpost"
top
Optionally provide pre-computed top(x)
...
Further arguments, passed to
grplot
Value
A plot of the top graph, with their marginal likelihoods
(without priors)
See Also
levelplot.bnpostmcmc,
bnpostmcmc, bnpost
rjbgoudie/structmcmc documentation built on Nov. 3, 2020, 3:41 a.m.
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Description Usage Arguments Value See Also
Description
Plot the the top() Bayesian Networks from a posterior distribution. The top graphs are those with the highest score with respect to the posterior distribution, which for converged MCMC will be most commonly encountered graph.
Usage
1 2 |
Arguments
x |
An object of class "bnpostmcmc" or "bnpost" |
top |
Optionally provide pre-computed top(x) |
... |
Further arguments, passed to
|
Value
A plot of the top graph, with their marginal likelihoods (without priors)
See Also
levelplot.bnpostmcmc,
bnpostmcmc, bnpost
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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