pcf.kern {denpro} | R Documentation |
Calculates a multivariate kernel estimate and gives the output as a piecewise constant function object.
pcf.kern(dendat, h, N, kernel = "epane", hw = NULL)
dendat |
n*d matrix of real numbers; the data matrix |
h |
positive real; smoothing parameter |
N |
vector of d positive dyadic integers; the dimension of the grid where the kernel estimate will be evaluated; we evaluate the estimate on a regular grid which contains the support of the kernel estimate |
kernel |
"epane" or "gauss"; the kernel is either the Bartlett-Epanechnikov product kernel or the standard Gaussian |
hw |
positive integer; parameter for time localized kernel estimation; gives the smoothing prameter for the temporal smoothing |
a piecewise constant function object, see the web site
Jussi Klemela
http://www.rni.helsinki.fi/~jsk/denpro/
dendat<-sim.data(n=100,type="mulmod") pcf<-pcf.kern(dendat,h=1,N=c(32,32)) dp<-draw.pcf(pcf) contour(dp$x,dp$y,dp$z,drawlabels=FALSE) pcf<-pcf.kern(dendat,h=1,N=c(32,32),hw=60) dp<-draw.pcf(pcf) contour(dp$x,dp$y,dp$z,drawlabels=FALSE)