[R] FW: problem with markov random field smooths in mgcv

[Simon Wood]

Hi Chris,

It's kind of a documentation glitch, a node is not supposed to be listed 
as its own neighbour (it causes the diagonal entries in the penalty 
matrix to be over-written by the wrong value). i.e. the neighbour list 
should be.

  NB <- list()
     NB$'East Timor' <- c(2,15)
     NB$Australia <- c(1,15)
     NB$'Sri Lanka' <-c(12,16)
     NB$Bangladesh <-c(12,13,16)
     NB$Philippines <- c(6,11,14,15,17)
     NB$Taiwan <- c(5,11)
     NB$Thailand <- c(8,10,12,13,14,15)
     NB$Vietnam <- c(7,10,11,14,15)
     NB$`South Korea` <- c(11)
     NB$Cambodia <- c(7,8)
     NB$China <- c(5,6,8,9,14)
     NB$India <- c(3,4,7,13,15,16)
     NB$Myanmar <- c(4,7,12,16)
     NB$Malaysia <- c(5,7,8,11,15)
     NB$Indonesia <- c(1,2,5,7,8,12,14)
     NB$HighSeas2 <- c(3,4,12,13)
     NB$HighSeas1 <- c(5)

I've fixed the help page and had the smooth constructor ignore 
auto-neighbours for the next release.

best,
Simon

   On 18/03/2020 07:44, Wilcox, Chris (O&A, Hobart) wrote:
> Hi all,
>      
>      I am trying to fit a model with a markov random field smooth in mgcv.  I am having some trouble with getting it to run, and in particular I am getting the message
>      
>      Error in initial.sp(w * x, S, off) : S[[1]] matrix is not +ve definite.
>      
>      After reading everything I could find on mrf, it sounds like there was a bug that was brought up with Simon Wood in 2012, due to differences between windows and linux, with the linus machine stopping due to this error, while windows was not.  I have not been able to find much else on it.  Any suggestions would be much appreciated.
>      
>      There is reproducible code below.
>      
>      Thanks
>      
>      Chris
>      
>      
>      library(mgcv)
>      
>      #create data
>      Country <- as.factor(c("Australia","Australia","Australia","Australia","Australia","Australia","Bangladesh","Bangladesh","Bangladesh",
>      "Bangladesh","Bangladesh","Bangladesh","Cambodia","Cambodia","Cambodia","Cambodia","Cambodia","Cambodia",
>      "China","China","China","China","China","China","East Timor","East Timor","East Timor",
>      "East Timor","East Timor","East Timor","HighSeas1","HighSeas1","HighSeas1","HighSeas1","HighSeas1","HighSeas1",
>      "HighSeas2","HighSeas2","HighSeas2","HighSeas2","HighSeas2","HighSeas2","China","China","China","China","China","China",
>      "India","India","India","India","India","India","Indonesia","Indonesia","Indonesia","Indonesia","Indonesia","Indonesia",
>      "Malaysia","Malaysia","Malaysia","Malaysia","Malaysia","Malaysia","Myanmar","Myanmar","Myanmar","Myanmar","Myanmar",
>      "Myanmar","Philippines","Philippines","Philippines","Philippines","Philippines","Philippines","South Korea","South Korea",
>      "South Korea","South Korea","South Korea","South Korea","China","China","China","China","China","China",
>      "Sri Lanka","Sri Lanka","Sri Lanka","Sri Lanka","Sri Lanka","Sri Lanka","Taiwan","Taiwan","Taiwan","Taiwan",
>      "Taiwan","Taiwan","Thailand","Thailand","Thailand","Thailand","Thailand","Thailand","Vietnam","Vietnam","Vietnam","Vietnam",
>      "Vietnam","Vietnam"))
>      
>      Count <- c(0,0,3,5,1,5,0,0,0,0,0,1,0,0,0,0,0,3,0,0,2,1,0,6,0,0,0,1,0,0,0,1,0,0,0,0
>      ,0,0,20,0,1,0,0,0,0,0,0,2,0,0,6,3,3,10,1,1,18,11,8,11,0,1,2,2,1,14,0,0,0,1,0,0
>      ,0,0,4,3,9,16,0,0,3,0,0,1,0,0,1,0,0,0,0,0,33,18,8,16,0,0,0,0,0,2,0,1,14,6,8,2
>      ,0,0,0,0,1,1)
>      
>      Data <- data.frame(Count,Country)
>      
>      #create neighbour matrix
>      NB <- list()
>      NB$'East Timor' <- c(1,2,15)
>      NB$Australia <- c(1,2,15)
>      NB$'Sri Lanka' <-c(3,12,16)
>      NB$Bangladesh <-c(4,12,13,16)
>      NB$Philippines <- c(5,6,11,14,15,17)
>      NB$Taiwan <- c(5,6,11)
>      NB$Thailand <- c(7,8,10,12,13,14,15)
>      NB$Vietnam <- c(7,8,10,11,14,15)
>      NB$`South Korea` <- c(9,11)
>      NB$Cambodia <- c(7,8,10)
>      NB$China <- c(5,6,8,9,11,14)
>      NB$India <- c(3,4,7,12,13,15,16)
>      NB$Myanmar <- c(4,7,12,13,16)
>      NB$Malaysia <- c(5,7,8,11,14,15)
>      NB$Indonesia <- c(1,2,5,7,8,12,14,15)
>      NB$HighSeas2 <- c(3,4,12,13,16)
>      NB$HighSeas1 <- c(5,17)
>      
>      #check levels and names match
>      all.equal(sort(names(NB)), sort(levels(Data$Country)))
>      
>      #try fitting GAM
>      m1 <- gam(Data$Count ~ s(Data$Country, bs = 'mrf', xt = list(nb = NB)))
>      
>      
>
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-- 
Simon Wood, School of Mathematics, University of Bristol, BS8 1TW UK
https://people.maths.bris.ac.uk/~sw15190/