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

[David Winsemius]

On 3/18/20 12:44 AM, 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)


I'm not seeing any spatial data being defined, so I'm puzzled by the 
expectation that this is yet a markov random field problem. You appear 
to be following the last part of the example code in 
?smooth.construct.mrf.smooth.spec {mgcv} without constructing your data 
set to match the structure of the `columb` example dataset.

str(columb)

#------------------

'data.frame': 49 obs. of  8 variables:
  $ area      : num  0.3094 0.2593 0.1925 0.0838 0.4889 ...
  $ home.value: num  80.5 44.6 26.4 33.2 23.2 ...
  $ income    : num  19.53 21.23 15.96 4.48 11.25 ...
  $ crime     : num  15.7 18.8 30.6 32.4 50.7 ...
  $ open.space: num  2.851 5.297 4.535 0.394 0.406 ...
  $ district  : Factor w/ 49 levels "0","1","2","3",..: 1 2 3 4 5 6 7 8 
9 10 ...
  $ x         : num  8.83 8.33 9.01 8.46 9.01 ...
  $ y         : num  14.4 14 13.8 13.7 13.3 ...


You are also committing a common R-beginner error in accessing columns 
of a data object directly in a formula while failing to use a data 
argument for a regression call.

-- 

David.

>      
>      #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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