predict.bdgraph: Predict function for 'S3' class "'bdgraph'"

In BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Predict function for S3 class "bdgraph"

Description

Provides predict values of the results for function bdgraph.

Usage

## S3 method for class 'bdgraph'
predict( object, iter = 1, ... )

Arguments

object	object of S3 class "bdgraph", from function bdgraph.
iter	number of predictions.
...	additional parameters.

Value

a matrix containing the predicted datasets, corresponding to the samples from the joint posterior disribtuion.

Author(s)

Reza Mohammadi [e-mail] and Ernst Wit

References

Mohammadi, R. and Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models, Journal of Statistical Software, 89(3):1-30, doi: 10.18637/jss.v089.i03

Mohammadi, A. and Wit, E. C. (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, Bayesian Analysis, 10(1):109-138, doi: 10.1214/14-BA889

Mohammadi, R., Massam, H. and Letac, G. (2021). Accelerating Bayesian Structure Learning in Sparse Gaussian Graphical Models, Journal of the American Statistical Association, doi: 10.1080/01621459.2021.1996377

Dobra, A. and Mohammadi, R. (2018). Loglinear Model Selection and Human Mobility, Annals of Applied Statistics, 12(2):815-845, doi: 10.1214/18-AOAS1164

Mohammadi, A. et al (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, Journal of the Royal Statistical Society: Series C, 66(3):629-645, doi: 10.1111/rssc.12171

See Also

bdgraph, bdgraph.mpl, bdgraph.dw

Examples

## Not run: 
# Generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 50, p = 6, size = 7, vis = TRUE )
   
bdgraph.obj <- bdgraph( data = data.sim )
   
predict( bdgraph.obj, iter = 20 )

## End(Not run)

BDgraph documentation built on Dec. 28, 2022, 1:54 a.m.