R: Plotting the results on multiple SIR model runs

plot.sir {igraph} | R Documentation

## Plotting the results on multiple SIR model runs

### Description

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.

### Details

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

### Value

Nothing.

### Author(s)

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

### 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.

### Examples

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

[Package igraph version 1.2.11 Index]