[R-sig-Geo] functions on kernel density estimation in pointpattern analysis-another two little problems

Tue Jun 26 10:23:59 CEST 2007

Dear Roger Bivand and Dan Putler,
  The result is really good, and i'm also clear with the choice of sigma in
density.ppp() function.
  I still have another two little problems:
*Q1*: How to change the background color into other color(e.g. white),or
specify all the colors into the user-defined colors?
myPal=brewer.pal(4,"Paired")   # For example, how to specify the 4 colors
with white,black,red,and blue.
I'm not familiar with RColorBrewer package, but i need it now. I'm now
learning it.

*Q2*: How to overlay the other .shp file with the result of kernel density
estimation?
The other .shp file is Qiupu River and Yangtze River. If i can overlay them
with the result of kernel density estimation,
  it'll be very clear that the cross part of Qiupu River and Yangtze River
has the highest density,which is true in reality and really
  what i want.
 Thanks very much.

On 6/26/07, Roger Bivand <Roger.Bivand at nhh.no> wrote:
>
> On Mon, 25 Jun 2007, Dan Putler wrote:
>
> Thanks, Dan, I agree that the bandwidths are the problem here. Often the
> image breaks settings are also very misleading for 2D density plots, so
> one needs to take care, as you show.
>
> Roger
>
> > Hi Zhi Jie,
>
> Below are some changes to your code which should make you much
> happier. It does involve the use of the RColorBrewer package to
> create a color palette that makes the plot a bit easier to see. As
> you can guess, the size of the standard deviation given to
> density.ppp was the problem. Your data is in the Xian 1980/3-degree
> Gauss-Kruger CM 117E projection (which is EPSG code 2384). Based on
> looking at things, the units of this projection are meters. Using the
> defaults of density.ppp, the standard deviation of the bandwidth of
> the smoother is 0.05 meters, far smaller than you wanted. The
> implicit assumption in density.ppp appears to be that the window of
> the study area is a unit square. The width of your study area is
> about 60Km, so to get a comparable bandwidth for your study area
> relative to the unit square, I upped the standard deviation to 3000
> meters.
>
> Here is my altered version of your code, you will need to change
> things back to the correct paths to the shapefile sets.
> ________
> library(spatstat)
> library(maptools)
> library(RColorBrewer)
>
> myPal=brewer.pal(12,"Paired") # An easily seen color palette
>
> guichi<-readShapePoly("~/Research/data/guichi2.shp")
> W <-as(as(guichi, "SpatialPolygons"), "owin")  #boundary polygons
>
> cases<-coordinates(readShapePoints("~/Research/data/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, 3000)
> plot(kdensity, col=myPal)
>
> rm(list=c("guichi","W","cases","pointcase","kdensity","myPal"))
> _______
>
> Dan
>
> On 25-Jun-07, at 7:49 AM, zhijie zhang wrote:
>
> > 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(ÿÿ)",ylab="y(ÿÿ)")
> > 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/
> > >
> > > _______________________________________________
> > > R-sig-Geo mailing list
> > > R-sig-Geo at stat.math.ethz.ch
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
> >
> >
> >
> > --
> > 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::
> > ::\_)::(..)::
> > :::::::)./:::
> > ::::::(_/::::
> > :::::::::::::
> > <data.rar>
> > <map.jpg>
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at stat.math.ethz.ch
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>
> --
> Roger Bivand
> Economic Geography Section, Department of Economics, Norwegian School of
> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand at nhh.no
>

-- 
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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