Error when trying to evaluate Markov Random Fields using mgcv::gam "mismatch between nb/polys supplied area names and data area names"

Question

I tried to implement this great blog post by Gavin Simpson using data downloaded from the cancensus package, but I get the following error when trying to evaluate the gam:

Error in smooth.construct.mrf.smooth.spec(object, dk$data, dk$knots) : 
  mismatch between nb/polys supplied area names and data area names
In addition: Warning message:
In if (all.equal(sort(a.name), sort(levels(k))) != TRUE) stop("mismatch 
between nb/polys supplied area names and data area names") :
  the condition has length > 1 and only the first element will be used

I have posted my minimal working example here. Any tips would be greatly appreciated.

Best, Zoltan

Answer 1

Found it -- You must make sure that you don't have any polygons with missing Y:

shp <- shp[!is.na(shp@data$Y), ]

Answer 2

I know you already found your answer, however I had the same error and a different problem, so I'll post my solution here for posterity.

(Note: I used the sf package instead of rgdal and spdep)

library(sf)
sh_terr <- st_read("your_shp.shp", stringsAsFactors = T) 

neighb <- st_touches(sh_terr, sparse = T) %>% 
  lapply(function(xx) sh_terr$FSA[xx] %>% factor(levels = levels(sh_terr$FSA))) %>% 
  set_names(sh_terr$FSA)

Your neighboring object structure should look like:

str(neighb[1:5])
List of 5
 $ G0A: Factor w/ 419 levels "G0A","G0C","G0E",..: 14 15 16 17 21 22 39 49 50 51 ...
 $ G0C: Factor w/ 419 levels "G0A","G0C","G0E",..: 3 6 67
 $ G0E: Factor w/ 419 levels "G0A","G0C","G0E",..: 2 6 65 67
 $ G0G: Factor w/ 419 levels "G0A","G0C","G0E",..: 5 16 62 70 271
 $ G0H: Factor w/ 419 levels "G0A","G0C","G0E",..: 4 14 16 68 70 71

And your spline formula:

Effect ~ s(FSA, bs = "mrf", xt = list(nb = neighb), k = 41, fx = TRUE)

It's all in the factors. FSA in your main data object of your gam must be factor, and your neighboring object structure should be a list of factors with as many levels as the TOTAL number of levels in your main data.