R0 defined in package "twinstim" class, which
computes mean numbers of infections caused by infected individuals depending on the event type
and marks attached to the individual, which contribute to the infection pressure
in the epidemic predictor of that class.R0(object, ...)## S3 method for class 'twinstim':
R0(object, newevents, trimmed = TRUE,
dimyx = NULL, eps = NULL, ...)
R0 method exists.data.frame of events for which the basic reproduction
numbers should be calculated. If omitted, it is calculated for the
original events from the fit. In this case, if
trimmed = TRUE (the default), the rtrimmed = TRUE) or over
the whole time-space domain R+ x R^2 (polyCub.midpoint).
If eps = NULL (the default)twinstim method.object corresponding to the rows of newevents (if
supplied) or the original fitted events including events of the prehistory."twinstim" class, the individual-specific mean
number $\mu_j$ of infections caused by individual (event) $j$
inside its theoretical (untrimmed) spatio-temporal range of interaction
given by its eps.t ($\epsilon$) and eps.s
($\delta$) values is defined as follows (cf. Meyer et al, 2012):
$$\mu_j = e^{\eta_j} \cdot \int_0^\epsilon g(t) dt \cdot
\int_{b(\bold{0},\delta)} f(\bold{s}) d\bold{s} .$$
Here, $b(\bold{0},\delta)$ denotes the disc centred at (0,0)' with
radius $\delta$, $\eta_j$ is the epidemic linear predictor,
$g(t)$ is the temporal interaction function, and $f(\bold{s})$
is the spatial interaction function.
Alternatively, the trimmed (observed) mean reproduction numbers
are obtain by integrating over the observed infectious domains of the
individuals, i.e. integrate $f$ over the intersection of the
influence region with the observation region W
(i.e. over ${ W \cap b(\bold{s}_j,\delta) } - \bold{s}_j$)
and $g$ over the intersection of the observed infectious period with
the observation period $(t_0;T]$ (i.e. over
$(0; \min(T-t_j,\epsilon)]$).