run | R Documentation |
SimBIID_model
objectWrapper function that compiles (if necessary) and runs
a SimBIID_model
object. Returns results in a
user-friendly manner as a SimBIID_run
object,
for which print()
and plot()
generics
are provided.
run( model, pars, tstart, tstop, u, tspan, nrep = 1, parallel = FALSE, mc.cores = NA )
model |
An object of class |
pars |
A named vector of parameters. |
tstart |
The time at which to start the simulation. |
tstop |
The time at which to stop the simulation. |
u |
A named vector of initial states. |
tspan |
A numeric vector containing the times at which to save the states of the system. |
nrep |
Specifies the number of simulations to run. |
parallel |
A |
mc.cores |
Number of cores to use if using parallel processing. |
An object of class SimBIID_run
, essentially a list
containing elements:
sums: a data.frame()
with summaries of the model runs. This
includes columns run
, completed
, t
, u*
(see help file for SimBIID_model
for more details);
runs: a data.frame()
object, containing columns: run
,
t
, u*
(see help file for SimBIID_model
for more details).
These contain time series counts for the simulations. Note that this will
only be returned if tspan = TRUE
in the original SimBIID_model
object.
bootEnd: a time point denoting when bootstrapped estimates end and predictions
begin (for predict.PMCMC()
method).
mparseRcpp
, print.SimBIID_runs
, plot.SimBIID_runs
## set up SIR simulation model transitions <- c( "S -> beta * S * I -> I", "I -> gamma * I -> R" ) compartments <- c("S", "I", "R") pars <- c("beta", "gamma") model <- mparseRcpp( transitions = transitions, compartments = compartments, pars = pars ) ## compile and run model sims <- run( model = model, pars = c(beta = 0.001, gamma = 0.1), tstart = 0, tstop = 100, u = c(S = 119, I = 1, R = 0) ) sims ## add tspan option to return ## time series counts at different ## time points model <- mparseRcpp( transitions = transitions, compartments = compartments, pars = pars, tspan = TRUE ) sims <- run( model = model, pars = c(beta = 0.001, gamma = 0.1), tstart = 0, tstop = 100, u = c(S = 119, I = 1, R = 0), tspan = seq(1, 100, length.out = 10) ) sims ## run 100 replicate simulations and ## plot outputs sims <- run( model = model, pars = c(beta = 0.001, gamma = 0.1), tstart = 0, tstop = 100, u = c(S = 119, I = 1, R = 0), tspan = seq(1, 100, length.out = 10), nrep = 100 ) sims plot(sims)
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