plot.sir

0th

Percentile

Plotting the results on multiple SIR model runs

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

Keywords
graphs
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.
Details

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

Value

  • Nothing.

References

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

See Also

sir for running the actual simulation.

Aliases
  • plot.sir
Examples
g <- sample_gnm(100, 100)
sm <- sir(g, beta=5, gamma=1)
plot(sm)
Documentation reproduced from package igraph, version 1.0.0, License: GPL (>= 2)

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