flex.test | R Documentation |
flex.test
performs the flexibly-shaped scan test
of Tango and Takahashi (2005).
flex.test( coords, cases, pop, w, k = 10, ex = sum(cases)/sum(pop) * pop, type = "poisson", nsim = 499, alpha = 0.1, longlat = FALSE, cl = NULL, lonlat = longlat, ... )
coords |
An n \times 2 matrix of centroid coordinates for the regions in the form (x, y) or (longitude, latitude) is using great circle distance. |
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. |
k |
An integer indicating the maximum number of regions to inclue in a potential cluster. Default is 10 |
ex |
The expected number of cases for each region. The default is calculated under the constant risk hypothesis. |
type |
The type of scan statistic to compute. The
default is |
nsim |
The number of simulations from which to compute the p-value. |
alpha |
The significance level to determine whether a cluster is signficant. Default is 0.10. |
longlat |
The default is |
cl |
A cluster object created by |
lonlat |
Deprecated in favor of |
... |
Not used. |
The test is performed using the spatial scan test based on the Poisson test statistic and a fixed number of cases. The first cluster is the most likely to be a cluster. If no significant clusters are found, then the most likely cluster is returned (along with a warning).
Returns a list of length two of class scan. The first element (clusters) is a list containing the significant, non-ovlappering clusters, and has the the following components:
Joshua French
Tango, T., & Takahashi, K. (2005). A flexibly shaped spatial scan statistic for detecting clusters. International journal of health geographics, 4(1), 11. Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics – Theory and Methods 26, 1481-1496.
print.smerc_cluster
,
summary.smerc_cluster
,
plot.smerc_cluster
,
scan.stat
, scan.test
data(nydf) data(nyw) coords <- with(nydf, cbind(longitude, latitude)) out <- flex.test( coords = coords, cases = floor(nydf$cases), w = nyw, k = 3, pop = nydf$pop, nsim = 49, alpha = 0.12, longlat = TRUE ) data(nypoly) library(sp) plot(nypoly, col = color.clusters(out))
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