baycn-class {baycn}

baycn class

Description

baycn class

Slots

burnIn

The percentage of MCMC iterations that will be discarded from the beginning of the chain.

chain

A matrix where the rows contain the vector of edge states for the accepted graph.

decimal

A vector of decimal numbers. Each element in the vector is the decimal of the accepted graph.

iterations

The number of iterations for which the Metropolis-Hastings algorithm is run.

posteriorES

A matrix of posterior probabilities for all three edge states for each edge in the network.

posteriorPM

A posterior probability adjacency matrix.

likelihood

A vector of log likelihood values. Each element in the vector is the log likelihood of the accepted graph.

stepSize

The number of iterations discarded between each iteration that is kept.

time

The runtime of the Metropolis-Hastings algorithm in seconds.