baycn class

`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.

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