Raster Prediction with factors in model

Hi,

I have a GAM model that contains factors in addition to smooth terms etc. I
would like to evaluate this at all points on a raster, but I can't seem to
get the predict.raster() function to pick up the values of my factors. I
have created a minimum (not) working example here, based on the example for
the predict() function.

Any suggestions in this direction would be appreciated.

Mark

# create a RasterStack or RasterBrick with with a set of predictor layers
logo <- brick(system.file("external/rlogo.grd", package="raster"))

# known presence and absence points
p <- 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)

a <- matrix(c(22, 33, 64, 85, 92, 94, 59, 27, 30, 64, 60, 33, 31, 9,
              99, 67, 15, 5, 4, 30, 8, 37, 42, 27, 19, 69, 60, 73, 3, 5, 21,
              37, 52, 70, 74, 9, 13, 4, 17, 47), ncol=2)

# extract values for points
xy <- rbind(cbind(1, p), cbind(0, a))
v <- data.frame(cbind(xy[,1], extract(logo, xy[,2:3])))
colnames(v)[1] <- 'pa'

#Convert blue layer to a factor
v$blue <- factor(v$blue < 200)

#build a model, here an example with glm
model <- glm(formula=pa~., data=v)

#Setup prediction objects
pred.b <- logo[[1:2]]
const.df <- data.frame(blue=TRUE)

#predict to a raster
r1 <- predict(pred.b, model, progress='text',
              const=const.df)


#Returns an error as follows:
# Error in `[.data.frame`(blockvals, , f[j]) : undefined columns selected

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