The function takes either an edgelist or an adjacency matrix and returns an
adjacency matrix with the reciprocity change statistic. This reciprocity
matrix can then be used as a predictor in the gHypEG regression.

reciprocity_stat(graph, nodes = NULL, zero_values = NULL)

## Arguments

graph |
A graph adjacency matrix or an edgelist. The edgelist needs to
have 3 columns: a sender vector, a target vector and an edgecount vector. |

nodes |
optional character/factor vector. If an edgelist is provied,
you have to provide a list of unique identifiers of your nodes in the graph.
This is because in the edgelist, isolates are usually not recorded.
If you do not specify isolates in your nodes object, they are excluded
from the analysis (falsifies data). |

zero_values |
optional numeric value. Use this to substitute zero-values
in your reciprocity change statistic matrix. Zero values in the predictors
are recognized in the gHypEG regression as structural zeros. To ensure this
does not happen, please recode your zero-values in all your predictors.
If `zero_values` is not specified, the minmal value divided by 10 is
used instead. |

## Value

Reciprocity change statistic matrix.

## See also