stcd {surveillance} | R Documentation |
Shiryaev-Roberts based prospective spatio-temporal cluster detection as in Assuncao & Correa (2009).
stcd(x, y,t,radius,epsilon,threshold)
x |
Vector containing spatial x coordinate of the events. |
y |
Vector containing spatial y coordinate of the events. |
t |
Vector containing the time points of the events. It is assumed that the vector is sorted (early->last). |
radius |
Radius of the cluster to detect. |
epsilon |
Relative change of event-intensity within the cluster to detect. See reference paper for an explicit definition. |
threshold |
Threshold limit for the alarm and should be equal to the desired Average-Run-Length (ARL) of the detector. |
Shiryaev-Roberts based spatio-temporal cluster detection based on the work in Assuncao and Correa (2009). The implementation is based on C++ code originally written by Marcos Oliveira Prates, UMFG, Brazil and provided by Thais Correa, UMFG, Brazil during her research stay in Munich. This stay was financially supported by the Munich Center of Health Sciences.
Note that the vectors x
, y
and t
need to be of the
same length. Furthermore, the vector t
needs to be sorted (to
improve speed, the latter is not verified within the function).
The current implementation uses a call to a C++ function to perform the actual computations of the test statistic. The function is currently experimental – data type and results may be subject to changes.
A list with three components
R |
A vector of the same length as the input containing the value of the test statistic for each observation. |
idxFA |
Index in the x,y,t vector causing a possible alarm. If no
cluster was detected, then a value of -1 is returned here. |
idxCC |
index in the x,y,t vector of the event containing the
cluster. If no cluster was detected, then a value of -1 is
returned here. |
M. O. Prates, T. Correa and M. Höhle
Assuncao, R. and Correa, T. (2009), Surveillance to detect emerging space-time clusters, Computational Statistics & Data Analysis, 53(8):2817-2830.
library("splancs") data(burkitt) #Parameters for the SR detection epsilon <- 0.5 # relative change within the cluster radius <- 20 # radius threshold <- 161 # threshold limit res <- stcd(burkitt$x,burkitt$y,burkitt$t,radius,epsilon,threshold) #Index of the event which.max(res$R >= threshold)