From: Rolf Turner <rolf.turner_at_xtra.co.nz>

Date: Sat, 16 Apr 2011 20:46:55 +1200

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sat 16 Apr 2011 - 08:49:12 GMT

Date: Sat, 16 Apr 2011 20:46:55 +1200

On 16/04/11 15:50, Gregory Ryslik wrote:

> Hi Everyone,

*>
**> I am trying to figure out the spatstat package for the first time and am having some trouble. Unfortunately, I can't post my data set but I'll hopefully post enough details for some help.
**>
**> I want to model the intensity of a spatial point process using 2 covariates from my data. After reading through the documentation, I have successfully created 2 "ppp" objects. The first ppp object is a list of coordinates where people exist and the second is where people do not exist as follows:
**>> people_exist
**> planar point pattern: 944 points
**> window: rectangle = [73, 135] x [18, 54] units
**>> people_empty
**> planar point pattern: 2828 points
**> window: rectangle = [73, 135] x [18, 54] units
**>
**> Now, I also have observed values for two covariates, Z1 and Z2 for both the 944 and 2828 points in dataframe form. Finally, following the documentation, I was able to create one quadrature Q, with 944 points and 2828 dummy points that correctly takes the points where we had an event (people_exist) and the points where we don't have an event (people_empty).
**>> people_quadrature
**> Quadrature scheme
**> 944 data points, 2828 dummy points
**> Total weight 1098.64
**>
**> How do I use the Quadrature to model my intensity based off of those two covariates and an intercept term alpha? In mathematical terms, if \lambda is my intensity function, I want to estimate \lambda(s;b) = exp(alpha + b_1 * Z_1 + b_2 * Z_2).
**>
**> Thank you for your help! I really appreciate it.
*

Your procedure seems to evince quite a bit of confusion in your mind about
what you are actually doing. To start with, one gets the impression
that you have

*two* point patterns ("people" and "no people"). But then, from your
quadrature

scheme it appears that you are treating the "no people" pattern as the dummy
points for the quadrature scheme.

You would then execute a command of the form

fit <- ppm(people_quadrature, ~ Z1 + Z2, covariates=covDf)

fit <- ppm(people_exist, ~ IZ1 + IZ2, covariates=list(IZ1=IZ1, IZ2=IZ2))

I.e. you just need the ``real'' point pattern (presumably a point
pattern of human

habitations) and the covariates expressed as (pixellated) images.

cheers,

Rolf Turner

P. S. The foregoing all assumes that the pattern of interest is a
realization of

an inhomogeneous ***Poisson*** process, with intensity depending (log
linearly)

upon the two covariates Z1 and Z2. There could of course be
*interaction* between

the points and the dependence upon covariates could be more complicated than
that proposed.

R. T.

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