
Hi,

I don't remeber if this is corrected in the current version of 
spatstat (please, actualize) but, anyway, I think you can troubleshot 
the problem with this:


io <- !is.na(slope.subset[xxx04, drop=F])

ppm(xxx04[io], ~ x + y + slope, Poison(), covariates = list(slope=slope.subset)



I hope this helps,

Marcelino



At 20:49 15/04/2008, Honey Giroday wrote:


>Hi All!
>
>I am a relatively new UseR and am currently using R 2.5.1 on a linux 
>operating system (I am connected to the linux system via remote 
>desktop connection).  I am trying to import a raster dataset (in 
>ASCII format) to fit as a covariate in a ppm.  However, I keep 
>getting this error message every time I got to fit the model.
>
>"Warning message:
>Values of covariate "slope" were NA or undefined at 1% (1 out of 
>80812) of the quadrature points.  Occurred while executing: 
>ppm(xxx04, ~ x + y + slope, Poison(), covariates = list(slope=slope.subset)"
>
>At first I thought the problem sprung from the alignment of my image
>(slope) with the object window of my point process 
>(xxx04).  However, I have the datasets are
>in the same projection (UTM zone 10), and I have set the owin for 
>the points and subset the slope covariate to the same extent.  I 
>have also viewed the slope and image datasets in a plot and they 
>appear to line up correctly (i.e. there are no points that are 
>outside the extent of the slope image).  Can anyone assist me with 
>understanding the cause of this error message and suggest a method 
>to rectify/troubleshoot this problem?  Please see the code below to 
>see the steps I went through to fit the ppm.  Your help would be
>much appreciated and thank you for your time in considering this issue.
>
>
>
>
>
>Sincerely,
>
>
>
>
>
>Honey-Marie Giroday, M.Sc. Candidate, A.Ag., B.I.T.
>
>University of Northern British Columbia
>
>
>
>
>
>#Read in shapefile data (2004, 2005, and 2006)
>mpb04 <- 
>readShapePoints("N:/data/original/mpb/licensees/final/2004mpb_licensees")
>
>#Extract X and Y coordinates from ShapePoints
>X <- mpb04$Easting
>Y <- mpb04$Northing
>
>#Read in site characteristic covariates (ASCII)
>slope <- 
>readAsciiGrid("N:/data/original/base_data/dem/bc/utm_tpi/slope20utm.txt", 
>as.image=TRUE)
>
>#Read in susceptibility covariates (ASCII)
>sus0 <- 
>readAsciiGrid("N:/data/original/susceptibilitydata/climate_factor/utm_tpi/sus0.txt", 
>as.image=TRUE)
>
>#Convert covariates from list class to image class
>image.slope <- as.im(slope)
>sus0 <- as.im(sus0)
>
>#Create object window for analysis from one of the susceptibility datasets
>sus0.win <- as.owin(sus0)
>
>#Subset site characteristic and landform datasets susceptibility boundary
>slope.subset <- image.slope[sus0.win, drop=FALSE]
>
>#Use cut command to make landform and susceptibility a factor!
>sus0.cut <- cut(sus0, 2)
>
>#Convert ShapePoints to point pattern manually
>xxx04 <- ppp(x=mpb04$Easting, y=mpb04$Northing, window=sus0.win)
>
>#Test if model fitting works
>fm1 <- ppm(xxx04, ~ x + y + slope, Poisson(), covariates=list(slope=slope))
>
>
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***************************************
Marcelino de la Cruz Rot
Depto. Biologia Vegetal
EUIT Agricola
Universidad Politecnica de Madrid
28040-Madrid
SPAIN
***************************************
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