edmst.zones  R Documentation 
edmst.zones
determines the zones for the early
stopping Dynamic Minimum Spanning Tree scan test
(edmst.test
). The function returns the
zones, as well as the associated test statistic, cases in
each zone, the expected number of cases in each zone, and
the population in each zone.
edmst.zones(
coords,
cases,
pop,
w,
ex = sum(cases)/sum(pop) * pop,
ubpop = 0.5,
ubd = 1,
longlat = FALSE,
cl = NULL,
progress = TRUE
)
coords 
An 
cases 
The number of cases observed in each region. 
pop 
The population size associated with each region. 
w 
A binary spatial adjacency matrix for the regions. 
ex 
The expected number of cases for each region. The default is calculated under the constant risk hypothesis. 
ubpop 
The upperbound of the proportion of the total population to consider for a cluster. 
ubd 
A proportion in (0, 1]. The distance of
potential clusters must be no more than 
longlat 
The default is 
cl 
A cluster object created by 
progress 
A logical value indicating whether a
progress bar should be displayed. The default is

Every zone considered must have a total population less
than ubpop * sum(pop)
. Additionally, the maximum
intercentroid distance for the regions within a zone must
be no more than ubd * the maximum intercentroid
distance across all regions
.
Returns a list with elements:
zones 
A list contained the location ids of each potential cluster. 
loglikrat 
The loglikelihood ratio for each zone (i.e., the log of the test statistic). 
cases 
The observed number of cases in each zone. 
expected 
The expected number of cases each zone. 
pop 
The total population in each zone. 
Joshua French
Costa, M.A. and Assuncao, R.M. and Kulldorff, M. (2012) Constrained spanning tree algorithms for irregularlyshaped spatial clustering, Computational Statistics & Data Analysis, 56(6), 17711783. <doi:10.1016/j.csda.2011.11.001>
data(nydf)
data(nyw)
coords < as.matrix(nydf[, c("longitude", "latitude")])
# find zone with max statistic starting from each individual region
all_zones < edmst.zones(coords,
cases = floor(nydf$cases),
nydf$pop, w = nyw, ubpop = 0.25,
ubd = .25, longlat = TRUE
)
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