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bnlearn (version 0.8)

bn class: The bn class structure

Description

The structure of an object of the bn S3 class.

Arguments

Details

An object of class bn is a list containing at least the following components:

  • learning: a list containing some information about the results of the learning algorithm. It's never changed afterward.
    • nodes: a list. Each element is named after a node and contains the following elements:
      • mb: the Markov blanket of the node (a vector of character strings).
      • nbr: the neighbourhood of the node (a vector of character strings).
    • arcs: the arcs of the Bayesian network (a two-column matrix, whose columns are labeledfromandto).
    • whitelist: a sanitized copy of thewhitelistparameter (a two-column matrix, whose columns are labeledfromandto).
    • blacklist: a sanitized copy of theblacklistparameter (a two-column matrix, whose columns are labeledfromandto).
    • test: the label of the conditional independence test or used by the learning algorithm (a character string). The label of the network score is used for score-based algorithms.
    • ntests: the number of conditional independence tests used in the learning (an integer value).
    • algo: the label of the algorithm used in the learning process (a character string), or "random/generated" for randomly generated or empty networks.
    • args: a list. The values of the parameters of either the conditional tests or the scores used in the learning process. Only the relevant ones are stored, so this may be an empty list.
      • alpha: the target nominal type I error rate (a numerical value) of the conditional independence tests.
      • iss: a positive numerical value, the imaginary sample size used by thebgeandbdescores.
      • phi: a character string, eitherheckermanorbottcher; used by thebgescore.
      • k: a positive numerical value, the penalty per parameter used by theaicandbicscores.
  • nodes: a list. Each element is named after a node and contains the following elements:
    • mb: the Markov blanket of the node (a vector of character strings).
    • nbr: the neighbourhood of the node (a vector of character strings).
    • parents: the parents of the node (a vector of character strings).
    • children: the children of the node (a vector of character strings).
  • arcs: the arcs of the Bayesian network (a two-column matrix, whose columns are labeledfromandto).