Under conditions of low cell density we used a spatial clustering analysis to group cells such that the distance between groups effectively constrained communication to cells within groups.
Firstly, it is the first study to examine the spatial distribution of suicide in Queensland at a LGA level using a spatial cluster analysis approach.
Using the Bernoulli model, a spatial cluster of infected farms was detected in La Pampa (38.38 S, 66.92 W; radius = 250 km; P < 0.05) (Fig. 3), where the risk for infection was nearly 2.6 (RR = 2.58; P < 0.05) times higher in farms located inside the cluster than in those located elsewhere.
EP microstate segments were defined by using a spatial k-means cluster analysis to identify the dominant map topographies in the group-averaged evoked potentials across the experimental conditions over time.
For the purely spatial analysis, a discrete Poisson probability model was used to scan for non-overlapping geographical areas (counties) with statistically significant high rates of suicide, using a maximum spatial cluster size of 50% of the total population at risk, as recommended by Kulldorff [ 24].
Using a maximum spatial cluster size of ≤10% of total population, the clusters for all cases and indigenous cases were identical to the analysis using a maximum spatial cluster size of ≤50% of total population.
Using a maximum spatial cluster size of ≤50% of the total population, 2 statistically significant clusters were identified for all cases.
Total under-five mortality rates (MR) were calculated and their geographical distributions were investigated using a spatial scan statistic to test for clusters of higher than average under-five mortality in both space and time.
TIDA was developed for application to imagery of native Eucalypt forests in Australia, and uses a 'top down' spatial clustering approach involving key steps designed to reduce the effects of crown segmentation.
Kuldroff's spatial scan statistic is a widely used spatial cluster analysis method (Kulldorff [1997]).
