[R-sig-Geo] functions on kernel density estimation in pointpattern analysis

zhijie zhang epistat at gmail.com
Mon Jun 25 16:49:59 CEST 2007 

Dear Roger Bivand,Tim Keitt, and Dan Putler,
  Thanks for your answers. I have tried density.ppp(spatstat) and
kernel2d(splancs), but the results are not very satisfied. I think there
should be a higher density in the blue part of the map in the attachment.
  My dataset has been put in the attachment and programs have been pasted in
the following, so that u can use and check it.
   I want to do the work like "non-parametric estimation of a spatially
varying intensity" in Diggle's book(2003.P.116-121).
  BTW, i'm not familiar with locfit,would u please also check it using
locfit? Thanks very much.
###############################################################################
                           Kernel density estimation--spatstat
################################################################################
library(sp)
library(foreign)
library(maptools)
library(mgcv)
library(spatstat)

guichi<-readShapePoly("d:/deleting/kernel/kernel/guichi2.shp")
W <-as(as(guichi, "SpatialPolygons"), "owin")  #boundary polygons

cases<-coordinates(readShapePoints("d:/deleting/kernel/kernel/cases.shp"))
#points
colnames(cases)<-c("x","y")
cases[1:2,]

#plot(W);points(cases)

pointcase <- ppp(cases[,1], cases[,2], window=W)  #generate the ppp object

kdensity<-density.ppp(pointcase, 0.05)
plot(kdensity)
*Q:*there are almost the same density in the whole area,but in fact it may
have a higher density in the blue part of the attached map? I think the
problem may the inappropriate value of sigma, how to determine its value?

################################################################################
                                 Kernel density estimation--splancs
################################################################################
library(sp)
library(splancs)
library(foreign)
library(maptools)

case<-readShapePoints("d:/deleting/kernel/kernel/cases.shp")
guichi<-readShapePoly("d:/deleting/kernel/kernel/guichi2.shp")

#Conversion
case_pts <- coordinates(case)
case <- as.points(case_pts)
splancs_poly <-
getPolygonCoordsSlot(getPolygonsPolygonsSlot(getSpPpolygonsSlot(guichi)[[1]])[[1]])


#to unpack the coordinates of the points and the single ring boundary
polymap(splancs_poly,xlab="x(米)",ylab="y(米)")
pointmap(case_pts, add=TRUE)

m<-mse2d(case,splancs_poly,nsmse=1000,range=5)  #plots the estimated mean
square error as a function of h0
plot(m$h[290:1000],m$mse[290:1000],type="l")

n<-which(m$mse==min(m$mse))
h0<-m$h[n]


#smooth variation
smooth<-kernel2d(case, splancs_poly, h0=h0, nx=100, ny=100)
polymap(splancs_poly)  #sets the axes correctly and draws the polygon
image(smooth,add=T)   #the smoothed image is superimposed
polymap(splancs_poly,add=T) #redrawn the polymap in order not to be obsured
by smooth image
*Q*:The result is still not satisfied,there must be something wrong with my
programs.







On 6/25/07, Dan Putler <putler at sauder.ubc.ca> wrote:
>
> Hi All,
>
> To add some detail to Roger's earlier, post density.ppp in the
> spatstat seems to be a very good answer to the original post since it
> is specifically designed to estimate a kernel density for a point
> process pattern. This function use a bivariate Gaussian smoother that
> lends itself to user configuration.
>
> Dan
>
> On 24-Jun-07, at 5:28 PM, Tim Keitt wrote:
>
> > I rather like locfit.
> >
> > THK
> >
> > On 6/24/07, zhijie zhang <epistat at gmail.com> wrote:
> >> Dear Friends,
> >>  Except kernel2d(splancs) function, are there any other functions
> >> on kernel
> >> density estimation in point pattern analysis? I use the kernel2d
> >> (splancs)
> >> function to anayze my dataset, and the result seems not to be very
> >> good.
> >>   Any suggestions or help in kernel density estimation of
> >> univariate or
> >> multivariate point process are greatly appreciated.
> >>   BTW, i mainly want ot do the kernel density estimation in both
> >> univariate and multivariate point process.
> >> --
> >> With Kind Regards,
> >>
> >> oooO:::::::::
> >> (..):::::::::
> >> :\.(:::Oooo::
> >> ::\_)::(..)::
> >> :::::::)./:::
> >> ::::::(_/::::
> >> :::::::::::::
> >> [********************************************************************
> >> ***]
> >> Zhi Jie,Zhang ,PHD
> >> Tel:86-21-54237149
> >> Dept. of Epidemiology,School of Public Health,Fudan University
> >> Address:No. 138 Yi Xue Yuan Road,Shanghai,China
> >> Postcode:200032
> >> Email:epistat at gmail.com
> >> Website: www.statABC.com
> >> [********************************************************************
> >> ***]
> >> oooO:::::::::
> >> (..):::::::::
> >> :\.(:::Oooo::
> >> ::\_)::(..)::
> >> :::::::)./:::
> >> ::::::(_/::::
> >> :::::::::::::
> >>
> >>         [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-Geo mailing list
> >> R-sig-Geo at stat.math.ethz.ch
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
> >
> >
> > --
> > Timothy H. Keitt, University of Texas at Austin
> > Contact info and schedule at http://www.keittlab.org/tkeitt/
> > Reprints at http://www.keittlab.org/tkeitt/papers/
> > ODF attachment? See http://www.openoffice.org/
> >
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>
>


-- 
With Kind Regards,

oooO:::::::::
(..):::::::::
:\.(:::Oooo::
::\_)::(..)::
:::::::)./:::
::::::(_/::::
:::::::::::::
[***********************************************************************]
Zhi Jie,Zhang ,PHD
Tel:86-21-54237149
Dept. of Epidemiology,School of Public Health,Fudan University
Address:No. 138 Yi Xue Yuan Road,Shanghai,China
Postcode:200032
Email:epistat at gmail.com
Website: www.statABC.com
[***********************************************************************]
oooO:::::::::
(..):::::::::
:\.(:::Oooo::
::\_)::(..)::
:::::::)./:::
::::::(_/::::
:::::::::::::
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