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

Tue, 24 Mar 2020 15:47:24 -0700 

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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and provide commented, minimal, self-contained, reproducible code.


--
Simon Wood, School of Mathematics, University of Bristol, BS8 1TW UK
https://people.maths.bris.ac.uk/~sw15190/

______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.






















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