Sentence examples for clustering of events from inspiring English sources

"What we saw in the 2015 data was a bump which was not hugely statistically significant, but nonetheless there was a bump, a clustering of events at a mass of about 750 GeV," said David Charlton, professor of particle physics, University of Birmingham and spokesperson for the Atlas Collaboration at Cern.

In Adelaide, there have been calls for the state government to separate out the clustering of events in February and March – but their modelling has found it's precisely this cluster which makes it so successful: the sum is greater than its parts.

Second, latent topic models allow for soft clustering of events.

The method can be used to calculate spatial, temporal, or spatiotemporal clustering of events (Kulldorff et al. [2005]).

Moreover, given the daily resolution of timestamps in IBC and the corresponding clustering of events on a given day, we strongly caution against the direct calibration of a Hawkes model even where robust timing signatures exist, simply because the resulting model fits will be (falsely) rejected by standard goodness-of-fit methods.

A clustering of events has been defined on the commonality of attributes describing events, where exact match of attributes causes events to be positioned in the same cluster, whereas a partial match causes a link to be described between events across their corresponding clusters as has been described in [106].

The spatial scan statistic is a method for measuring spatial clustering of event data within adjacent geographic areas and over closely overlapping time periods (Naus [1965]).

Identification and Clustering of Event Patterns From In Vivo Multiphoton Optical Recordings of Neuronal Ensembles.

Unit-specific random effects are used to handle clustering of event times within statistical units.

An unit specific random effect or frailty term is introduced to the proportional hazards model to account for potential clustering of event times within a statistical unit.

Of note, hierarchical clustering of event-related timecourses was employed (e.g., Ploran et al., 2007; Church et al., 2011), in conjunction with statistical testing, to identify and characterize candidate regions.