cumtvd: Cumulative total variation distance.
In rjbgoudie/structmcmc: Structural inference for Bayesian Networks and Variable Selection.
Description
Usage
Arguments
See Also
Examples
Description
method description
Usage
1
2
Arguments
exactgp
...
bnpostmcmclist
...
start
...
end
...
nbin
...
...
Further arguments passed to method
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
x1 <- factor(c(1, 1, 0, 1, 1, 1))
x2 <- factor(c(0, 1, 0, 1, 0, 1))
x3 <- factor(c(0, 1, 0, 0, 0, 0))
x <- data.frame(x1 = x1, x2 = x2, x3 = x3)
exact <- posterior(x, "exact")
exactgp <- gp(exact)
mcmc1 <- posterior(x, "mc3", nSamples = 1000, nBurnin = 100)
mcmc2 <- posterior(x, "mc3", nSamples = 1000, nBurnin = 100)
tvd <- cumtvd(exactgp = exactgp,
bnpostmcmclist = bnpostmcmc.list(mcmc1, mcmc2))
rjbgoudie/structmcmc documentation built on Nov. 3, 2020, 3:41 a.m.
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.
Description Usage Arguments See Also Examples
Description
method description
Usage
1 2 |
Arguments
exactgp |
... |
bnpostmcmclist |
... |
start |
... |
end |
... |
nbin |
... |
... |
Further arguments passed to method |
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 | x1 <- factor(c(1, 1, 0, 1, 1, 1))
x2 <- factor(c(0, 1, 0, 1, 0, 1))
x3 <- factor(c(0, 1, 0, 0, 0, 0))
x <- data.frame(x1 = x1, x2 = x2, x3 = x3)
exact <- posterior(x, "exact")
exactgp <- gp(exact)
mcmc1 <- posterior(x, "mc3", nSamples = 1000, nBurnin = 100)
mcmc2 <- posterior(x, "mc3", nSamples = 1000, nBurnin = 100)
tvd <- cumtvd(exactgp = exactgp,
bnpostmcmclist = bnpostmcmc.list(mcmc1, mcmc2))
|
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.