Как исправить ошибку с марковскими случайными полями в mgcv - PullRequest
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Как исправить ошибку с марковскими случайными полями в mgcv

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/ 18 марта 2020

Я пытаюсь подобрать модель со случайным марковским полем, гладким в mgcv. У меня возникли некоторые проблемы с его запуском, и, в частности, я получаю сообщение

Ошибка в initial.sp (w * x, S, off): S [[1]] матрица не + ve определенное.

После прочтения всего, что я смог найти в MRF, похоже, что в 2012 году в Simon Wood была обнаружена ошибка, связанная с различиями между Windows и Linux, с Машина Линуса останавливается из-за этой ошибки, пока windows не было. Я не смог найти что-то еще по этому поводу. Будем благодарны за любые предложения.

Ниже приведен воспроизводимый код. 


    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)))
...