gamlockedTrain {STAR} | R Documentation |
Smooths a lockedTrain
object using a gam
model with the Poisson
family after binning the object.
gamlockedTrain(lockedTrain, bw = 0.001, bs = "cr", k = 100, ...) ## S3 method for class 'gamlockedTrain': print(x, ...) ## S3 method for class 'gamlockedTrain': summary(object, ...) ## S3 method for class 'gamlockedTrain': plot(x, xlab, ylab, main, xlim, ylim, col, lwd, ...)
lockedTrain |
a lockedTrain object. |
bw |
the bin width (in s) used to generate the observations on which the gam fit will be performed. See details below. |
bs |
the type of splines used. See s . |
k |
the dimension of the basis used to represent the smooth
psth. See s . |
x |
an gamlockedTrain object. |
object |
an gamlockedTrain object. |
xlim |
a numeric (default value supplied). See
plot . |
ylim |
a numeric (default value supplied). See plot . |
xlab |
a character (default value supplied). See plot . |
ylab |
a character (default value supplied). See plot . |
main |
a character (default value supplied). See plot . |
lwd |
line width used to plot the estimated density. See plot . |
col |
color used to plot the estimated density. See plot . |
... |
additional arguments passed to gam in
gamlockedTrain . Not used in print.gamlockedTrain and
summary.gamlockedTrain . Passed to plot in
plot.gamlockedTrain . |
gamlockedTrain
essentially generates a smooth version of the
histogram obtained by hist.lockedTrain
. The Idea is to
build the histogram first with a "too" small bin width before fitting
a regression spline to it with a Poisson distribution of the observed
counts.
A list of class gamlockedTrain
is returned by
gamlockedTrain
. This list has the following components:
gamFit |
the gamObject generated. |
Time |
the vector of bin centers. |
nRef |
the number of spikes in the reference train. See
hist.lockedTrain . |
testFreq |
the mean frequency of the test neuron. See
hist.lockedTrain . |
bwV |
the vector of bin widths used. |
CCH |
a logical which is TRUE if a cross-intensity was
estimated and FALSE in the case of an auto-intensity. |
call |
the matched call. |
print.gamlockedTrain
returns the result of print.gam
applied to the component gamFit
of its argument.
summary.gamlockedTrain
returns the result of summary.gam
applied to the component gamFit
of its argument.
Christophe Pouzat christophe.pouzat@gmail.com
Wood S.N. (2006) Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press.
lockedTrain
,
plot.lockedTrain
,
gam
## load e070528spont data set data(e070528spont) ## create a lockedTrain object with neuron 1 as reference ## and neuron 3 as test up to lags of +/- 250 ms lt1.3 <- lockedTrain(e070528spont[[1]],e070528spont[[3]],laglim=c(-1,1)*0.25) ## look at the cross raster plot lt1.3 ## build a histogram of it using a 10 ms bin width hist(lt1.3,bw=0.01) ## do it the smooth way slt1.3 <- gamlockedTrain(lt1.3) plot(slt1.3) ## do some check on the gam fit summary(slt1.3) gam.check(gamObj(slt1.3))