Description Usage Arguments Details Value See Also Examples

View source: R/ergm.allstats.R

`ergm.allstats`

produces a matrix of network statistics for an
arbitrary `statnet`

exponential-family random graph model. One
possible use for this function is to calculate the exact loglikelihood
function for a small network via the `ergm.exact`

function.

1 2 3 4 5 6 7 |

`formula` |
an |

`zeroobs` |
Logical: Should the vectors be centered so that the network
passed in the |

`force` |
Logical: Should the algorithm be run even if it is determined that the problem may be very large, thus bypassing the warning message that normally terminates the function in such cases? |

`maxNumChangeStatVectors` |
Maximum possible number of distinct values of the vector of statistics. It's good to use a power of 2 for this. |

`...` |
further arguments; not currently used. |

The mechanism for doing this is a recursive algorithm, where the number of
levels of recursion is equal to the number of possible dyads that can be
changed from 0 to 1 and back again. The algorithm starts with the network
passed in `formula`

, then recursively toggles each edge twice so that
every possible network is visited.

`ergm.allstats`

should only be used for small networks, since the
number of possible networks grows extremely fast with the number of nodes.
An error results if it is used on a directed network of more than 6 nodes or
an undirected network of more than 8 nodes; use `force=TRUE`

to
override this error.

Returns a list object with these two elements:

`weights` |
integer of counts, one for each row of |

`statmat` |
matrix in which each row is a unique vector of statistics. |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
# Count by brute force all the edge statistics possible for a 7-node
# undirected network
mynw <- network(matrix(0,7,7),dir=FALSE)
system.time(a <- ergm.allstats(mynw~edges))
# Summarize results
rbind(t(a$statmat),a$weights)
# Each value of a$weights is equal to 21-choose-k,
# where k is the corresponding statistic (and 21 is
# the number of dyads in an 7-node undirected network).
# Here's a check of that fact:
as.vector(a$weights - choose(21, t(a$statmat)))
# Simple ergm.exact outpuf for this network.
# We know that the loglikelihood for my empty 7-node network
# should simply be -21*log(1+exp(eta)), so we may check that
# the following two values agree:
-21*log(1+exp(.1234))
ergm.exact(.1234, mynw~edges, statmat=a$statmat, weights=a$weights)
``` |

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