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In the first step, we estimate the well-established short time clustering.
Furthermore, if the connectivity of the AROB with four-port connection is allowed, two constant time clustering algorithms can be also derived using N4 and N3 processors, respectively.
This time interval describes well the time clustering between large earthquakes [ Parsons, 2002; Faenza et al., 2008].
Moreover, several clusters reflect local epidemics, as shown by isolates from the same geographical area and time clustering together in the tree.
Therefore, it is important to develop clustering algorithms which are accurate and can provide real time clustering in large data sets.
It also does not explain time clustering of relapse intervals or heterologous genotypes in relapses.
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For the Burkitt's lymphoma data, Bailey and Gatrell used the k-function based approach to analyze this data set and concluded that significant space-time clustering existed [32].
Jk increases when there is space-time clustering.
This epidemiologic spreading pattern indicates that time clustering is probably at least as effective in detecting clusters as combined space-time clustering.
Support for this hypothesis may be provided by a finding of space-time clustering.
It has been argued that population shifts may cause artificial space-time clustering [ 28, 29].
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