new function predict, package raster
Dear Isabelle,
Thanks for the detailed report. So it is a bug after all. This is
probably fixed in raster 1.7-8 (on CRAN for win and lin now).
At least the below works for me (model with 2 variables, one is a factor).
Robert
library(raster)
# create a RasterStack (a set of predictor rasters)
logo <- stack(system.file("external/rlogo.grd", package="raster"))
presence <- matrix(c(48, 48, 48, 53, 50, 46, 54, 70, 84, 85, 74, 84,
95, 85, 66, 42, 26, 4, 19, 17, 7, 14, 26, 29, 39, 45, 51, 56, 46, 38,
31, 22, 34, 60, 70, 73, 63, 46, 43, 28), ncol=2)
background <- cbind(runif(250)*(xmax(logo)-xmin(logo))+xmin(logo),
runif(250)*(ymax(logo)-ymin(logo))+ymin(logo))
xy <- rbind(cbind(1, presence), cbind(0, background))
v <- cbind(xy[,1], extract(logo, xy[,2:3]))
colnames(v)[1] <- 'presback'
v=data.frame(v[,1:3])
v[,3] <- as.factor(v[,3])
model <- glm(formula=presback~., data=v)
r <- predict(logo, model, progress='text')
On Fri, Dec 3, 2010 at 3:26 AM, isabelle boulangeat
<isabelle.boulangeat at gmail.com> wrote:
Hi, Thanks for all these explanations. I misunderstood the use of the "const". In my case, I just need to deal with an explicative variable that is spatially explicit but categorial. I should use a raster with numbers that correspond to my factor's levels. However, I still have some problems to predict using the categorial variable (raster package, version 1.7-7) my code : predict(rasStack, model=model_fac) Error message : Erreur dans v[cells, ] <- predv : Here are details on the raster Stack and the data.frame containing explicative variables to fit the model (expl). rasStack class?????? : RasterStack nlayers???? : 2 nrow??????? : 3137 ncol??????? : 1951 ncell?????? : 6120287 projection? : +proj=lcc +lat_1=45.89891888888889 +lat_2=47.69601444444444 +lat_0=46.8 +lon_0=2.337229166666667 +x_0=600000 +y_0=2200000 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +towgs84=0,0,0 min value?? : -1280???? 1 max value?? : 462?? 7 extent????? : 784300, 979400, 1858800, 2172500? (xmin, xmax, ymin, ymax) resolution? : 100, 100? (x, y) layerNames(rasStack) [1] "temp"?? "corine" unique(getValues(rasStack[[2]])) [1] NA? 6? 5? 1? 7? 4? 2? 3 str(expl) 'data.frame':?? 11396 obs. of? 2 variables: ?$ temp? : num? -78.4 -282.9 -172.1 -173.6 -83.2 ... ?$ corine: Factor w/ 7 levels "1","2","3","4",..: 6 4 3 4 5 6 6 4 5 6 ... unique(expl$corine) [1] 6 4 3 5 7 2 1 Levels: 1 2 3 4 5 6 7 model_fac <- glm(resp ~ ., data=expl, family="binomial") Any idea? 2010/12/2 Robert J. Hijmans <r.hijmans at gmail.com>
Isabelle,
If you use a factor that is represented by numbers on a grid you can
just fit the model (with the factor variable as factor), and the
predict function will then make a factor from the predictor layers
(i.e. there is nothing else you need to do). Where this can go wrong
is if you have factor levels on your raster that were not in the data
used to fit the model. You can get something like:
Error in model.frame.default(Terms, newdata, na.action = na.action,
xlev = object$xlevels) :
?factor 'x' has new level(s): ?2, 3, 4, 5,
Which means that you first need to remove those levels (set to NA)
from your predictor raster. (I will try to automate that problem away,
in raster::predict, eventually)
The argument "const" is for factor type variables for which you do not
have spatial data. Hence they could be considered 'constant' in some
contexts. For example, with fish observation data you might have a
model that predicts abundance from a number of variables including the
method used to catch the fish. Say a factor variable "method" with
levels "A" or "B". You can then do something like
method = factor("A")
predict(raster, model, const=method)
Robert
On Thu, Dec 2, 2010 at 9:02 AM, isabelle boulangeat
<isabelle.boulangeat at gmail.com> wrote:
Hello, I am trying to use the recently updated function "predict" from the package raster. I would like to use the field "const", as one of my variable is categorial. I have an error message but I can't find where is the problem. Error message : Erreur dans `[.data.frame`(blockvals, , f[i]) : undefined columns selected code : Pred_fac <- predict(rasStack, model=model_fac, predict=predict.glm, progress='text', const=factorDF) rasStack is a RasterStack and contains only one layer with one explicative variable. the layer name is the same as in the model. factorDF is a data.frame and contains only one column with one explicative variable. the column name is the same as in the model. the dimensions are the same : the number of rows in the data frame correspond to the number of cells in the raster. Does someone succeed to use this function with the new field "const" ? Thanks for help, Cheers, Isabelle. -- Isabelle Boulangeat, PhD student Ecosystem dynamics and plant traits Bureau 203, +33 (0) 476 635 733 Laboratoire d'?cologie Alpine (LECA) Grenoble, France lab' s website : http://www-leca.ujf-grenoble.fr/ my website : http://j.boulangeat.free.fr/ ? ? ? ?[[alternative HTML version deleted]]
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-- Isabelle Boulangeat, PhD student Ecosystem dynamics and plant traits Bureau 203, +33 (0) 476 635 733 Laboratoire d'?cologie Alpine (LECA) Grenoble, France lab' s website : http://www-leca.ujf-grenoble.fr/ my website : http://j.boulangeat.free.fr/