Plotting the results on multiple SIR model runs

This function can conveniently plot the results of multiple SIR model simulations.

Usage

# S3 method for class 'sir'
plot(
  x,
  comp = c("NI", "NS", "NR"),
  median = TRUE,
  quantiles = c(0.1, 0.9),
  color = NULL,
  median_color = NULL,
  quantile_color = NULL,
  lwd.median = 2,
  lwd.quantile = 2,
  lty.quantile = 3,
  xlim = NULL,
  ylim = NULL,
  xlab = "Time",
  ylab = NULL,
  ...
)

Arguments

x: The output of the SIR simulation, coming from the sir() function.
comp: Character scalar, which component to plot. Either ‘NI’ (infected, default), ‘NS’ (susceptible) or ‘NR’ (recovered).
median: Logical scalar, whether to plot the (binned) median.
quantiles: A vector of (binned) quantiles to plot.
color: Color of the individual simulation curves.
median_color: Color of the median curve.
quantile_color: Color(s) of the quantile curves. (It is recycled if needed and non-needed entries are ignored if too long.)
lwd.median: Line width of the median.
lwd.quantile: Line width of the quantile curves.
lty.quantile: Line type of the quantile curves.
xlim: The x limits, a two-element numeric vector. If NULL, then it is calculated from the data.
ylim: The y limits, a two-element numeric vector. If NULL, then it is calculated from the data.
xlab: The x label.
ylab: The y label. If NULL then it is automatically added based on the comp argument.
...: Additional arguments are passed to plot(), that is run before any of the curves are added, to create the figure.

Value

Nothing.

Details

The number of susceptible/infected/recovered individuals is plotted over time, for multiple simulations.

References

Bailey, Norman T. J. (1975). The mathematical theory of infectious diseases and its applications (2nd ed.). London: Griffin.

Author

Eric Kolaczyk (http://math.bu.edu/people/kolaczyk/) and Gabor Csardi csardi.gabor@gmail.com.

Examples


g <- sample_gnm(100, 100)
sm <- sir(g, beta = 5, gamma = 1)
plot(sm)