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

```
# S3 method for 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,
...
)
```

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.

Nothing.

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

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

`sir`

for running the actual simulation.

```
# NOT RUN {
g <- sample_gnm(100, 100)
sm <- sir(g, beta=5, gamma=1)
plot(sm)
# }
```

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