prob | R Documentation |

Methods for accessing or changing the local probability distributions and for accessing the local prior and posterior distributions

prob(x,df,...) ## S3 method for class 'node' prob(x,df,nw,...) ## S3 method for class 'network' prob(x,df,...) localprob(nw) localprob(nw,name) <- value localprior(node) localposterior(node)

`x` |
an object of class |

`df` |
a data frame, where the columns define the variables. A
continuous variable should have type |

`nw` |
an object of class |

`node` |
an object of class |

`name` |
a string, which gives the node name. |

`...` |
additional arguments for specific methods. |

`value` |
If the node is continuous, this is a numeric vector with the conditional variance and the conditional regression coefficients arising from a regression on the continuous parents, using data. If the node has discrete parents, it is a matrix with a row for each configuration of the discrete parents. If the node is discrete, it is a multiway array which gives the conditional probability distribution for each configuration of the discrete parents. |

The `prob`

methods add local
probability distributions to
each node. If the node is continuous, this is a
numeric vector with
the conditional variance and the conditional regression coefficients
arising from a regression on the continuous parents, using data. If
the node has discrete parents, `prob`

is a matrix with a row
for each configuration of the discrete parents. If the node is
discrete, `prob`

is a multiway array which gives the conditional
probability distribution for each configuration of the discrete
parents. The generated `prob`

can be replaced to match the prior
information available.

`localprob`

returns the probability distribution
for each node in the network.

In a learned network, the local prior and posterior can be accessed
for each node using `localprior`

and `localposterior`

.

Susanne Gammelgaard Bottcher,

Claus Dethlefsen rpackage.deal@gmail.com.

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