Sentence examples for randomness clustering from inspiring English sources

In the panels without confidence envelopes (left side), thick grey lines represent large American beech trees, dashed black lines represent large trees of all other species, and dotted horizontal lines indicate complete spatial randomness (clustering above, repulsion below).

Normalized univariate K-functions, where maximal L r -r vaL r -rbovalues 99% CI for complete spabove randomness indicatheclustering at that value of r (number of membrane sheets analyzed per condition, n = 17).

These results suggest that the Clark-Evans statistic is more sensitive to departures from randomness other than clustering, such as lineaments and anisotropy.

These methods, which have been reviewed in a number of monographs or special issues (e.g., Alexander and Boyle 1996) are typically used on a localized scale, mostly to study the spatial distribution of cases around a point source or different patterns of randomness or clustering of the cases in relation to those of controls.

where ( widehat{L}(d kern0.5em =kern0.5em 0 ) suggests randomness, ( widehat{L}(d kern0.5em >kern0.5em 0 )implies clustering, and ( widehat{L}(d kern0.5em

To assess the non-randomness of the strains clustering according to susceptibility status, we computed the ratio of the mean of the distances among susceptible strains to the mean of the distances between all susceptible and resistant strains.

Secondly, the randomness of cluster head selection can cause that some cluster heads share burden of nodes unbalance and aggravate some cluster head node's burden.

The resulting coefficient of aggregation (Ag) indicates randomness if Ag = 1, clustering if Ag > 1, and regular spacing or dispersion if Ag < 1 (Hopkins and Skellam 1954).

A Moran's I value near +1.0 indicates clustering; 0 indicates randomness; and a value near -1.0 indicates dispersion.

What most of us think of as randomness is occurrences that are evenly distributed — the opposite of clustering.

To investigate space-time clustering, the null hypothesis was spatio-temporal randomness, i.e. that case farms were distributed without clustering in space and time.