plot.spikeTrain {STAR} | R Documentation |
Adds a counting process display to the classical raster plot of single spike trains.
## 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 spikeTrain object or a vector which can be
coerced to such an object. |
xlab |
a character. The x label. |
ylab |
a character. The y label. |
main |
a character. The title. |
xlim |
a numeric. See plot . |
ylim |
a numeric. See plot . |
do.points |
see plot.stepfun . |
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 rug . |
... |
additional arguments passed to plot , see
plot and plot.stepfun . |
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 christophe.pouzat@gmail.com
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
## Not run: data(ShallowShocks) plot(as.spikeTrain(ShallowShocks$Date), xlab="Time (days)", main="Shallow Shocks Counting Process of Ogata 1988") ## End(Not run)