On 07/06/17 22:22, Seth Flaxman wrote:
I've got the intensity of an inhomogeneous Poisson process (fit using
some new methods I'm working on, so not created by spatstat) as an
image object, the observed point pattern as a ppp object, and I'd like
to call residuals.ppm to compute residuals. Is there a simple way to
create a fitted point process model (ppm) from an image and points so
I can pass this directly to residuals.ppm?
Sorry for the long delay in responding.
There are two ways to do this:
[1] Fit a model using the putative intensity as an offset:
fit1 <- ppm(X ~ offset(log(lam)))
where 'lam' is the pixel image of intensity, and 'X' is the point pattern.
Then do:
res <- residuals(fit1)
[2] Fit some other model (e.g. just a constant intensity model) and use
the argument 'fittedvalues' of residuals.ppm to specify the fitted
intensity values.
fit2 <- ppm(X ~ 1, forcefit=TRUE)
res <- residuals(fit2, fittedvalues=lam[quad.ppm(fit2)])
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
