amei (version 1.0-7)

plot.epiman: Plotting Epidemic Trajectories and Costs

Description

These functions provide a visualization of the evolution of an epidemic, or multiple epidemics obtained via Monte Carlo, and the associated costs of the vaccination strategy employed

Usage

"plot"(x, type = c("epi", "costs", "params", "fracs",  "stops"), showd = FALSE, showv = FALSE, prior = FALSE, main = NULL, ylim = NULL, tp = NULL, ...)
"plot"(x, type = c("epi", "costs", "fracs", "stops"),  showd = FALSE, showv = FALSE, main = NULL, ylim = NULL, ...)

Arguments

x

the object to be plotted, either of class "MCepi" or "epiman"

type

indicates the type of plot to be produced, including the epidemic trajectory/ies ("epi", the default), cost(s), estimated distribution(s) of parameters ("params", only in the case of "epiman"-class objects), the fraction vaccinated at each time step ("fracs"), and the vaccination (stopping) threshold ("stops")

main

optional title argument for the plot. If not specified, then an automatically generated default is used depending on the type of plot specified

ylim

optional limit for the y axis of the plot, applies only to type="cost"..

tp

this argument only applies to plot.epiman with type = "params" where it should be a list with scalar entries $b, $k, $nu, and $mu indicating the true parameter entries for the evolution of the epidemic to be added (for comparison) to the posterior density plots

showd

logical indicating if deaths should be shown in the trajectory plots when type = "epi"

showv

indicates if vaccinations should be shown in the trajectory plot

prior

indicates whether the prior density should be added to the plots when type = "params", otherwise ignored

...

additional arguments passed to plot

Value

The only output of this function is beautiful plots

Details

The functions documented here support visualization of "MCepi"-class objects which are generated by the MCepi and MCmanage function, and "epiman"-class objects are generated by the manage function. In both cases they enable a visualization of the evolution of the resulting epidemic(s) and costs associated with deaths, vaccinations, etc.

References

D. Merl, L.R. Johnson, R.B. Gramacy, and M.S. Mangel (2010). “amei: An R Package for the Adaptive Management of Epidemiological Interventions”. Journal of Statistical Software 36(6), 1-32. http://www.jstatsoft.org/v36/i06/ D. Merl, L.R. Johnson, R.B. Gramacy, M.S. Mangel (2009). “A Statistical Framework for the Adaptive Management of Epidemiological Interventions”. PLoS ONE, 4(6), e5807. http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005807

See Also

MCepi, manage, MCmanage

Examples

## for examples of the usage of these functions,
## please see the documentation for the functions
## listed in the See Also section, above