varianceTime {STAR} | R Documentation |
Performs Variance-Time Analysis for a Spike Train (or any univariate time series) assuming a Poisson Process with the same Rate as the Spike Train.
varianceTime(spikeTrain, CI = c(0.95, 0.99), windowSizes) is.varianceTime(obj) ## S3 method for class 'varianceTime': plot(x, style = c("default", "Ogata"), unit = "s", xlab, ylab, main, sub, xlim, ylim, ...)
spikeTrain |
a spikeTrain object or a vector which can be
coerced to such an object. |
obj |
a object to test against a varianceTime object. |
x |
a varianceTime object. |
CI |
a numeric vector with at most two elements. The coverage probability of the confidence intervals. |
windowSizes |
a numeric increasing vector of positive numbers. The window sizes used to split the spike train. |
style |
a character. The style of the plot, "default" or "Ogata" . |
unit |
a character. The unit in which the spike times are expressed. |
xlab |
a character. The x label. |
ylab |
a character. The y label. |
main |
a character. The title. |
sub |
a character. The subtitle. |
xlim |
a numeric. See plot . |
ylim |
a numeric. See plot . |
... |
see plot . |
See Fig. 5 of Ogata (1988) for details. The confidence intervals are obtained with a Normal approximation of the Poisson distribution.
varianceTime
returns a list of class varianceTime
with the following elements:
s2 |
numeric vector of empirical variance. |
sigma2 |
numeric vector of expected variance under the Poisson hypothesis. |
ciUp |
a numeric vector or a 2 rows matrix with the upper limits of the confidence interval(s). |
ciLow |
a numeric vector or a 2 rows matrix with the lower limits of the confidence interval(s). |
windowSizes |
numeric vector of window sizes actually used. |
CI |
a numeric vector, the coverage probabilities of the confidence intervals. |
call |
the matched call |
plot.varianceTime
is used for its side effect: a graph is
produced.
is.varianceTime
returns TRUE
if its argument is a
varianceTime
object and FALSE
otherwise.
Christophe Pouzat christophe.pouzat@gmail.com and Chong Gu chong@stat.purdue.edu for a correction on the sampling variance of the variance of a normal distribution.
Ogata, Yosihiko (1988) Statistical Models for Earthquake Occurrences and Residual Analysis for Point Processes. Journal of the American Statistical Association 83: 9-27.
acf.spikeTrain
,
renewalTestPlot
## Replicate (almost) Fig. 5 of Ogata 1988 data(ShallowShocks) vtShallow <- varianceTime(ShallowShocks$Date,,c(5,10,20,40,60,80,seq(100,500,by = 25))*10) is.varianceTime(vtShallow) plot(vtShallow, style="Ogata")