Sentence examples for for significant clusters from inspiring English sources
A flux diagram summarizing how it works can be seen in Fig. 4. OSLOM consists of three phases: First, it looks for significant clusters, until convergence; Second, it analyzes the resulting set of clusters, trying to detect their internal structure or possible unions thereof; Third, it detects the hierarchical structure of the clusters.
These methods use different approaches (semi-parametric to parametric) to test for significant clusters.
We took a threshold of cluster-wise p values of 0.05 as the criterion for significant clusters.
As a third example, we used WordCluster to search for significant clusters of olfactory receptor (OR) genes, the largest multigene family in multicellular organisms whose members are known to be clustered within vertebrate genomes [ 18, 19].
We thus developed the StretchFinder algorithm that tests for significant clustering of consecutive conserved codon sites.
The first of the two algorithms tested for significant clustering of births.
Maximum χ is a substitution distribution method that searches for significant clustering of substitutions at putative recombination break points (Maynard Smith 1992).
Then, mapping coordinates of orphaned reads along with various SAM fields were extracted and used as an input to insertion site scoring scheme for significant cluster detection.
Non-parametric MANOVA were conducted in R [ 45] using the 'adonis' command line in the 'vegan' package [ 46], in order to test for significant clustering of different dietary guilds and of taxonomic orders within the morphospace.
Additionally, a spatial econometrics model can be considered that applies a spatiotemporal methodology for the purpose of studying the dynamics of the Gini coefficient in the country and for detecting significant clusters of states with similar Gini coefficients.
In this study of pediatric physical and psychosocial outcomes we demonstrated the utility of a spatial scan statistic for identifying significant clusters of high- and low-risk areas of a poor recovery after injury.
