Description Usage Arguments Value Examples

A version of random.bn.fit which generates a graph based on degree distribution and beta distribution for probabilities

1 | ```
biased.bn.fit(nodes, beta.est, in.degree.distr, bn.graph)
``` |

`nodes` |
character vector of node names |

`beta.est` |
the beta distribution parameters for different degrees of a node. Should be a list where [[2]] corresponds to 2-dimenstional contingency table (i.e. one parent, one output). It contains a data.frame with columns shape1, shape2 for the beta distribution, and rows are degrees of freedom (in this case 2, when P(Out=0|Parent=0) and P(Out=0|Parent=1)) |

`in.degree.distr` |
a vector with degree distribution for all the nodes in the network (names are ignored, and degree is randomly sampled from this vector) |

`bn.graph` |
if the graph structure is already available, then the graph structure in object of class "bn" |

a list of two elements: `bn`

- a `bn`

object which contains the structure and
`bn.fit`

- a `bn.fit`

object with filled in conditional probabilities

1 2 3 4 5 6 | ```
# nodes, conditional probability distribution, an indegree distribution
nodes = letters[1:5]
beta.est = list(data.frame(shape1=2,shape2=3), data.frame(shape1=c(2,4), shape2=c(5,2)), data.frame(shape1=c(1,2,3,4), shape2=c(3,2,1,2)))
in.degree.distr = c(0, 1, 1, 2, 2)
# make a random graph using these parameters
biased.bn.fit(nodes, beta.est, in.degree.distr)
``` |

ddgraph documentation built on Nov. 17, 2017, 10:50 a.m.

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