Bayesian-DM-code-examples/FMD_spatial_worked_examples_Rcode_ABDM.txt at master · Andrew9Lawson/Bayesian-DM-code-examples · GitHub

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#######################################
####Bayesian Disease Mapping examples
#######################################


Preliminaries

library(INLA)

### need graphics tools

library(maptools)
library(spdep)


setwd("C:/..............................................................................")
source("fillmap.R")


################################################
## FMD example
################################################

FMDframe<-list(n=138,
count=c(1,0,1,0,2,3,1,0,1,0,3,2,0,3,1,6,1,10,2,1,8,4,4,1,1,
3,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,
0,0,0,1,1,1,0,0,0,0,0,0,2,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0),pop=c( 26,19,28,42,55,30,45,20,35,73,35,5,24,30,17,13,12,61,13,19,30,10,7,29,31,23,54,42,21,34,13,6,5,15,33,15,4,4,15,15,12,24,9,17,4,6,28,14,50,17,4,8,28,9,12,20,33,5,3,12,11,11,24,6,9,10,4,8,19,16,14,3,8,8,13,28,21,18,12,19,19,12,24,12,15,6,10,35,7,8,11,7,8,9,13,59,5,2,26,2,3,6,3,7,12,5,25,6,15,7,7,22,68,5,13,30,35,17,9,120,8,17,22,33,20,7,18,84,38,6,20,25,13,31,14,60,18,7 ))

FMDmap<-readSplus("FMD_splusMAP.txt")
plot(FMDmap)

attach(FMDframe)
rate<-count/pop

#######################################
### map of crude rates
#######################################

fillmap(FMDmap,"crude rate map",rate,n.col=6)

ind<-seq(1:138)
formula1<-count~1+f(ind,model="iid",param=c(2,1))
res1<-inla(formula1,family="binomial",data=FMDframe,Ntrials=pop,
control.compute=list(dic=TRUE))

summary(res1)

UH<-res1$summary.random$ind[,2]
fillmap(FMDmap,"posterior mean UH component",UH,n.col=4)

fit<-res1$summary.fitted.values$mean
resid<-count-fit

fillmap(FMDmap,"estimated crude residuals",resid,n.col=4)

linPred<-res1$summary.linear.predictor$mean
prob<-exp(linPred)/(1+exp(linPred))

fillmap(FMDmap,"posterior mean infection probability",prob,n.col=4)

###################################################