Estimation of the parent matrix of nodes from data. The frequency of node edges is obtained by fitting networks consistent to randomly generated node orders.

1 2 3 4 5 |

`data` |
a |

`pert` |
a binary |

`maxParentSet` |
an |

`parentSizes` |
an |

`maxComplexity` |
an |

`nodeCats` |
a |

`parentsPool` |
a list of parent sets to choose from |

`fixedParents` |
a list of parent sets to choose from |

`score` |
a |

`weight` |
a |

`maxIter` |
an |

`numThreads` |
an |

`echo` |
a boolean that sets on/off some functional progress and debug information |

The function performs `niter`

calls of `cnSearchOrder`

for randomly generated node orders (uniformly over the space of all possible node orders), selects networks according to `score`

and sum their parent matrices weighted by `weight`

. Three scoring criteria are currently supported: "BIC", "AIC" and maximum complexity for any other value of `score`

. The `weight`

can be
1) "likelihhod", then the parent matrices are multiplied by the network likelihood,
1) "score", then the parent matrices are multiplied by the exponential of the network score,
3) any other value of `weight`

uses multiplier 1. In this case
the entries in the output `matrix`

count the presence of the corresponding parent-child pairs.

The function can runs `numThreads`

number of parallel threads each processing different order.
`cnSearchHist`

function can be useful for empirical estimation of the relationships in some multivariate categorical data.

A `matrix`

N. Balov

1 2 3 4 5 6 | ```
library(sdnet)
cnet <- cnRandomCatnet(numnodes=8, maxpars=3, numcats=2)
psamples <- cnSamples(object=cnet, numsamples=100)
mhisto <- cnSearchHist(data=psamples, pert=NULL,
maxParentSet=2, maxComplexity=100)
mhisto
``` |

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