BayesNetBP (version 1.6.1)

AbsorbEvidence: Absorb evidence into the model

Description

Absorb evidence into the model

Usage

AbsorbEvidence(tree, vars, values)

Arguments

tree

a '>ClusterTree object

vars

a vector of the names of observed variables

values

a list of observed values of the variables. Aside from a single value, The element of the list can also be a vector of likelihood values

Value

'>ClusterTree object with the evidence absorbed

Details

Absorb multiple types and pieces of evidences into a '>ClusterTree object. The discrete compartment of the '>ClusterTree will be automatically propagated after evidence absorption, so that the object will be ready for making queries and absorbing additional evidence.

References

Cowell, R. G. (2005). Local propagation in conditional Gaussian Bayesian networks. Journal of Machine Learning Research, 6(Sep), 1517-1550.

Lauritzen, S. L., & Spiegelhalter, D. J. (1988). Local computations with probabilities on graphical structures and their application to expert systems. Journal of the Royal Statistical Society. Series B (Methodological), 157-224.

Yu H, Moharil J, Blair RH (2020). BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks. Journal of Statistical Software, 94(3), 1-31. <doi:10.18637/jss.v094.i03>.

Examples

# NOT RUN {
data(liver)
tree.init.p <- Initializer(dag=liver$dag, data=liver$data,
                           node.class=liver$node.class,
                           propagate = TRUE)
tree.post <- AbsorbEvidence(tree.init.p, c("Nr1i3", "chr1_42.65"), list(1,"1"))

# }