Description Usage Arguments Details Value Author(s) References See Also Examples

Adds a counting process display to the classical raster plot of single spike trains.

1 2 3 4 5 6 7 | ```
## S3 method for class 'spikeTrain'
plot(x, xlab = "Time (s)", ylab = "Cumulative Number of Events",
main = paste("Counting Process of",deparse(substitute(x))),
xlim = c(floor(x[1]), ceiling(x[length(x)])),
ylim = c(0, length(x) + 1),
do.points = ifelse(length(x) < 100, TRUE, FALSE),
addMeanRate = TRUE, addRug = TRUE, ...)
``` |

`x` |
a |

`xlab` |
a character. The x label. |

`ylab` |
a character. The y label. |

`main` |
a character. The title. |

`xlim` |
a numeric. See |

`ylim` |
a numeric. See |

`do.points` |
see |

`addMeanRate` |
should the expected counting process for a Poisson process with the same rate be added to the plot? |

`addRug` |
should a rug representation be added at teh bottom of
the plot? See |

`...` |
additional arguments passed to |

The counting process is obtained by a call to `stepfun`

.
When `xlab`

, `ylab`

, `main`

, `xlim`

or `ylim`

is (are) missing, default values are used.

Nothing is returned, `plot.spikeTrain`

is used for its side effect, a
plot is generated on the current graphic device.

Christophe Pouzat [email protected]

D. R. Cox and P. A. W. Lewis (1966) *The Statistical Analysis of
Series of Events*. John Wiley and Sons.

Brillinger, D. R. (1988) Maximum likelihood analysis of spike trains
of interacting nerve cells. *Biol. Cybern.* **59**: 189–200.

Johnson, D.H. (1996) Point process models of single-neuron
discharges. *J. Computational Neuroscience* **3**: 275–299.

`as.spikeTrain`

,
`is.spikeTrain`

,
`print.spikeTrain`

,
`summary.spikeTrain`

,
`renewalTestPlot`

,
`varianceTime`

,
`stepfun`

,
`plot.stepfun`

,
`rug`

1 2 3 4 5 6 7 | ```
## Not run:
data(ShallowShocks)
plot(as.spikeTrain(ShallowShocks$Date),
xlab="Time (days)",
main="Shallow Shocks Counting Process of Ogata 1988")
## End(Not run)
``` |

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