predict with glmer where new data is a Raster Stack of fixed efefcts

Question

I have constructed models in glmer and would like to predict these on a rasterStack representing the fixed effects in my model. my glmer model is in the form of:

m1<-glmer(Severity ~ x1 + x2 + x3 + (1 | Year) + (1 | Ecoregion), family=binomial( logit ))

As you can see, I have random effects which I don't have as spatial layer - for example 'year'. Therefore the problem is really predicting glmer on rasterStacks when you don't have the random effects data random effects layers. If I use it out of the box without adding my random effects I get an error.

 m1.predict=predict(object=all.var, model=m1, type='response',  progress="text", format="GTiff") 
Error in predict.averaging(model, blockvals, ...) :       

Answer 1

Your question is very brief, and does not indicated what, if any, trouble you have encountered. This seems to work 'out of the box', but perhaps not in your case. See ?raster::predict for options.

library(raster)   
# example data. See ?raster::predict
logo <- brick(system.file("external/rlogo.grd", package="raster"))
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)
xy <- rbind(cbind(1, p), cbind(0, a))
v <- data.frame(cbind(pa=xy[,1], extract(logo, xy[,2:3])))
v$Year <- sample(2000:2001, nrow(v), replace=TRUE) 


library(lme4)
m <- lmer(pa ~ red + blue + (1 | Year), data=v)

# here adding Year as a constant, as it is not a variable (RasterLayer) in the RasterStack object
x <- predict(logo, m, const=(data.frame(Year=2000)))

Answer 2

If you don't have the random effects, just use re.form=~0 in your predict call to predict at the population level:

x <- predict(logo, m, re.form=~0) 

works without complaint for me with @RobertH's example (although I don't know if correctly)