An inertia effect refers to the tendency for dyads to repeatedly interact
with each other (tie-oriented model) or for actors to repeatedly choose the
same actor as receiver of their events (actor-oriented model). The statistic
at timepoint t for dyad (i,j) resp. receiver j is
equal to the number of (i,j) events before timepoint t.
Optionally, a scaling method can be set with scaling
. By scaling the
inertia count by the outdegree of the sender ("prop"), the statistic refers
to the fraction of messages send by actor i that were send to actor j. If
actor i hasn't send any messages yet it can be assumed that every actor is
equally likely to receive a message from i and the statistic is set equal to
1/(n-1), where n refers to the number of actors. The resulting statistic is
similar to the "FrPSndSnd" statistic in the R package 'relevent', or the
persistence statistic in Section 2.2.2 of Butts (2008). Note that this
scaling method is only defined for directed events.