plotFit.RdThis function simulates the model under theta, generates observation
and plot them against the data. Since simulation and observation processes
can be stochastic, nReplicates can be plotted.
plotFit(
  fitmodel,
  theta,
  initState,
  data,
  nReplicates = 1,
  summary = TRUE,
  alpha = min(1, 10/nReplicates),
  allVars = FALSE,
  nonExtinct = NULL,
  observation = TRUE,
  plot = TRUE
)a fitmodel object
named numeric vector. Values of the parameters. Names should
match fitmodel$thetaNames.
named numeric vector. Initial values of the state
variables. Names should match fitmodel$stateNames.
data frame. Observation times and observed data. The time column
must be named "time" and the observation column must be named
"obs".
numeric, number of replicated simulations.
logical. If TRUE, the mean, median as well as the 50th
and 95th percentile of the trajectories are plotted (default). If
FALSE, all individual trajectories are plotted (transparency can be
set with alpha).
transparency of the trajectories (between 0 and 1).
logical, if FALSE only the observations are plotted.
Otherwise, all state variables are plotted.
character vector. Names of the infected states which must
be non-zero so the epidemic is still ongoing.  When the names of these
states are provided, the extinction probability is plotted by computing the
proportion of faded-out epidemics over time.  An epidemic has faded-out
when all the infected states (whose names are provided) are equal to 0.
This is only relevant for stochastic models.  In addition, if summary
== TRUE, the summaries of the trajectories conditioned on non-extinction
are shown. Default to NULL.
logical, if TRUE simulated observation are
generated by rTrajObs.
if TRUE the plot is displayed, and returned otherwise.
if plot == FALSE, a list of 2 elements is returned:
simulations data.frame of nReplicates
  simulated observations.
plot the plot of the fit.