edgep {BiDAG}

Estimating posterior probabilities of single edges

Description

This function estimates the posterior probabilities of edges by averaging over a sample of DAGs obtained via an MCMC scheme.

Usage

edgep(MCMCchain, pdag = FALSE, burnin = 0.2, endstep = 1)

Arguments

MCMCchain

an object of class partitionMCMC, orderMCMC or iterativeMCMC, representing the output of structure sampling function partitionMCMC or orderMCMC (the latter when parameter chainout=TRUE;

pdag

logical, if TRUE (FALSE by default) all DAGs in the MCMCchain are first converted to equivalence class (CPDAG) before the averaging

burnin

number between 0 and 1, indicates the percentage of the samples which will be discarded as ‘burn-in’ of the MCMC chain; the rest of the samples will be used to calculate the posterior probabilities; 0.2 by default

endstep

number between 0 and 1; 1 by default

Value

a square matrix with dimensions equal to the number of variables; each entry [i,j] is an estimate of the posterior probability of the edge from node i to node j

Author(s)

Polina Suter

Examples

Bostonscore<-scoreparameters("bge", Boston)
## Not run: 
samplefit<-sampleBN(Bostonscore, "order")
edgesposterior<-edgep(samplefit, pdag=TRUE, burnin=0.2)

## End(Not run)