Hello,
I am interested in using Morans I for different time intervals to detect
disease clusters.
Ultimately I would like to use CUSUM - or similar monitoring statistic to
monitor the results of Morans I - similar to the work by
Rogerson (2005) Spatial Surveillance and Cummulative Sum Methods in Spatial and
Syndromic Surveillance for Public Health.
Thus far - thanks to the list I have Morans I running in a loop for each day
(however I found that on some days no data is recorded, this caused an error to
get around this error I included an elseif statement to skip the calculation
for days where no disease notifications are recorded.)
I am just wondering if anyone has code/advice for the best way to apprach the
next stage of monitoring Morans I over different time intervals for the
detection of abnormal clusters. My code thus far is below - I would also like
to assemble the results in a neat table if anyone has tips for this I would alo
appreciate it as I am rather new to R!
Thanks
Serryn
T1<-read.dbf("ob.dbf")
N <- colnames(T1)
T2nb <- read.gal("PC.gal",override=TRUE)
col.W <- nb2listw(T2nb, style="W")
for(i in seq(N)) {
Vec1 <- spNamedVec(N[i+7], T1)
Svec1<-sum(Vec1)
ifelse ( Svec1> 0, res[i]<-moran.test(spNamedVec(N[i+7], T1), col.W,
zero.policy=TRUE), res[i]<-"NULL")
}
print(res)
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