ctsdag: Transition sequence equivalent class

In robertness/bninfo: Queries and information theoritic operations on Bayesian networks.

Description

Convert a dag to its transition sequence equivalence class, given a interventions. If a beta argument is provided, the algorithm assumes you working with a Bayesian score that does not have uniform prior. In this case, the members of the traditional PDAG equivalence class do not have the same posterior. So to preserve posterior equivalence, edges with skewed prior direction probability (probability of one direction greater than another) remain directed in the PDAG.

Usage

ctsdag(dag, interventions = NULL, beta = NULL)

Arguments

a	dag to be converted to a tsdag
The	interventions used in calculating the tsdag, defaults to NULL, which is the same as cpdag().
beta.	beta is a data frame with columns from, to and prob specifying the prior probability for a set of arcs. A uniform probability distribution is assumed for the remaining arcs. This is the same argument of score-related functions in bnlearn.

robertness/bninfo documentation built on May 27, 2019, 10:32 a.m.