Thank you for clarification!

Yury


2012/6/25 <Adrian.Baddeley@csiro.au>

> Rolf is correct: rhohat does not apply to categorical or discrete-valued
> covariates.
>
> Use quadratcount(X, tess=covariate) for a discrete covariate
>
> Prof Adrian Baddeley FAA
> CSIRO Mathematics, Informatics & Statistics
> Leeuwin Centre, 65 Brockway Rd, Floreat WA 6014, Australia
> tel +61 8 9333 6177 skype adrian.baddeley
> ________________________________________
> From: Rolf Turner [r.turner@auckland.ac.nz]
> Sent: Monday, 25 June 2012 8:09 AM
> To: Yury Ryabov
> Cc: r-sig-geo@r-project.org; Baddeley, Adrian (CMIS, Floreat)
> Subject: Re: [R-sig-Geo] spatstat: rhohat and classified raster
>
> If I understand your question correctly, it would appear that you are
> trying
> to apply rhohat() in an inappropriate context.  Your covariate seems to
> have
> discrete values; rhohat() is applicable only to continuous covariates.
> Moreover
> the theory on which rhohat() is based requires that the spatial cumulative
> distribution function of the covariate be *differentiable*.  A (fairly
> minimal?)
> sufficient condition for this is that the covariate be differentiable
> with non-zero
> gradient.
>
> See:
>
>     "Nonparametric estimation of the dependence of a spatial point process
>      on spatial covariates" by  Adrian Baddeley, Ya-Mei Chang, Yong
> Song and
>      Rolf Turner, in Statistics and its Interface, vol. 5, no. 2, 2012,
> pp. 221-236.
>
>     cheers,
>
>         Rolf Turner
>
> On 25/06/12 08:15, Yury Ryabov wrote:
> > Hi!
> >
> > I have an issue with interpretation of the results of "rhohat" function
> > (spatstat package). I use a classified raster as a covariate to my point
> > process. A raster is a land cover image with 300 m resolution. There are
> > several classes with values like 10, 20, 50, 100 etc. - all are multiple
> of
> > 10.
> >
> > The result of rhohat (http://image.bayimg.com/fapcmaadf.jpg)
> demonstrates
> > two peaks at values 135 and 165. Despite the fact that all raster values
> > are multiple of 10 and so there are no such values as 135 and 165, there
> > are also no such values as 130, 140, 160 or 170 (see histogram:
> > http://image.bayimg.com/fapcpaadf.jpg).
> >
> > So the question is what did I get and why? And is it correct to use a
> > classified raster as a covariate in "rhohat"?
> >
> > Here is the code (P is a ppp):
> >
> >> gl <- readAsciiGrid("/some_path/land_cover.asc", as.image=TRUE,
> >>       proj4string= CRS("+proj=tmerc +lat_0=0 +lon_0=33 +k=1 +x_0=6500000
> >> +y_0=0 +ellps=krass
> >
>  +towgs84=23.92,-141.27,-80.9,-0,0.35,0.82,-0.12
> >> +units=m +no_defs"))
> > glim <- as.im(gl)
> >> plot(rhohat(P, glim, covname="LandCover"),
> >>   xlab= "Global Land Cover",
> >>   legendpos = "topleft",
> >>   legendargs=list(bg="transparent"),
> >>   main = NULL)
> >
> > Best regards,
> > Yury Ryabov
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
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> > R-sig-Geo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>
>

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