[R-sig-Geo] Problem re-projecting Spatstat ppm model from lonlat to utm

[Ben Madin]

G'day all,

I have been using the ppm() function to try (mainly successfully) to fit an outbreak pattern from the spatstat library (1-22)

This was giving me results that were consistent with my observations, showing a trend related to a village density and increasing towards the east of the region. However, the scalebar was somewhat out of range, and I've realised I was working in longitude/latitude for my coordinates. 

I've transformed all of the data to utm, and gone through the same process, but when I try to fit the same model, I'm getting the following messages:

fit2.utm <- ppm(outbreaks.utm.ppp, ~ x + y + dens, covariates=list(dens=vill.dens.utm), use.gam=TRUE)
Warning messages:
1: In countingweights(id, areas) :
 Some tiles with zero area contain points
2: In countingweights(id, areas) : Some weights are zero

The two (one) data sets are given below :
> summary(outbreaks.ll.ppp)
Marked planar point pattern: 2231 points
Average intensity 12.9 points per square unit  
Multitype:
       frequency proportion intensity
A             222    0.09950    1.2800
Asia1           7    0.00314    0.0403
O            1090    0.48900    6.2800
Unknown       912    0.40900    5.2600

Window: polygonal boundary
single connected closed polygon with 2222 vertices
enclosing rectangle: [92.20499, 109.46484]x[1.269528, 28.546524]units
Window area =  173.539 square units 

*** 36 illegal points stored in attr(,„rejects‰) ***
> summary(outbreaks.utm.ppp)
Marked planar point pattern: 2102 points
Average intensity 1.01e-09 points per square unit  
Multitype:
       frequency proportion intensity
A             215    0.10200  1.03e-10
Asia1           6    0.00285  2.88e-12
O            1000    0.47600  4.80e-10
Unknown       880    0.41900  4.22e-10

Window: polygonal boundary
single connected closed polygon with 2222 vertices
enclosing rectangle: [417539.8, 2308845.2]x[142732, 3166241]units
Window area =  2.08442e+12 square units 

*** 165 illegal points stored in attr(,„rejects‰) ***



The result of the two models are given below :

> fit2.ll
Nonstationary multitype Poisson process
Possible marks: 
A Asia1 O Unknown

Trend formula: ~x + y + dens

Fitted coefficients for trend formula:
 (Intercept)             x             y          dens 
0.3513215637  0.0141986623 -0.0176586862  0.0004128483 

                Estimate         S.E. Ztest       CI95.lo       CI95.hi
(Intercept)  0.3513215637 4.494623e-01       -0.5296082814  1.2322514088
x            0.0141986623 4.211134e-03   ***  0.0059449912  0.0224523335
y           -0.0176586862 2.966964e-03   *** -0.0234738292 -0.0118435432
dens         0.0004128483 4.701333e-05   ***  0.0003207039  0.0005049927
Warning message:
model was fitted by gam(); asymptotic variance calculation ignores this 
> fit2.utm
Nonstationary multitype Poisson process
Possible marks: 
A Asia1 O Unknown

Trend formula: ~x + y + dens

Fitted coefficients for trend formula:
 (Intercept)             x             y          dens 
-2.193521e+01  1.991195e-07 -1.734678e-07  5.609414e+00 

Warning message:
model was fitted by gam(); asymptotic variance calculation ignores this 

and any attempt to plot fit2.utm fails - I suspect this is to do with 'empty' cells or the cell intensity? Is there some way around this?

cheers

Ben


sessionInfo()
R version 2.13.0 Patched (2011-05-26 r55996)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_AU.UTF-8/en_AU.UTF-8/C/C/en_AU.UTF-8/en_AU.UTF-8

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] spatstat_1.22-3     RandomFields_2.0.45 deldir_0.0-14      
 [4] mgcv_1.7-6          rgdal_0.6-33        Cairo_1.4-9        
 [7] surveillance_1.2-1  Matrix_0.999375-50  msm_1.0.1          
[10] vcd_1.2-11          colorspace_1.1-0    MASS_7.3-13        
[13] maptools_0.8-9      lattice_0.19-30     foreign_0.8-44     
[16] spc_0.4.0           xtable_1.5-6        rgeos_0.1-4        
[19] stringr_0.5         sp_0.9-83           zoo_1.6-5          
[22] RColorBrewer_1.0-5  RPostgreSQL_0.1-7   DBI_0.2-5          

loaded via a namespace (and not attached):
[1] mvtnorm_0.9-9991 nlme_3.1-101     plyr_1.5.2       splines_2.13.0  
[5] survival_2.36-9  tools_2.13.0