Sentence examples for multivariate measures from inspiring English sources

Numerous methods have been developed to analyze these complex recordings, including uni-variate (characterizing single channels), bi-variate (comparing channel pairs) and multivariate measures.

Multivariate measures of bone destruction, as proxies for levels of on-site competition and thus predation risk, show little systematic relationship with patterns of lithic discard and butchery.

Results indicated differences among habitats in structure of assemblages, in mean abundance of common taxa and in univariate and multivariate measures of spatial variation at the scale of shores.

The effects of MPAs and habitat were assessed with a multifactorial sampling design; hypotheses were tested about differences in structure of assemblages, in mean abundance of common taxa and in univariate and multivariate measures of spatial variation.

Indeed, recent work in nonlinear dynamical systems resulted in new application-independent multivariate measures of synchronization [32], [33], [34], [35].

This measure is strongly correlated with multivariate measures of body size (PC1 and centroid size) calculated from this data based on 17 landmark measurements (cf. [19]).

To examine the association between the Gait Deviation Index (GDI), a multivariate measure of overall gait impairment, and measures of both community walking performance and walking capacity within the clinic setting in ambulatory children with cerebral palsy.

Further it was determined through structural equation modeling that 70% of the variance in the online students' levels of cognitive presence, a multivariate measure of learning, can be modeled based on their reports of their instructors' skills in fostering teaching presence and their own abilities to establish a sense of social presence.

The S-estimator was proved to be a robust and easily scalable multivariate measure of synchronization, highly sensitive even with a reasonably small amount of data.

The multivariate measure of size (centroid) of each specimen is computed as the square root of the sum of squared inter-landmark distances [65].

While PLA is a symmetric measure of (phase) relations inside a pair of signals, the multivariate measure of PDC was developed to reveal the temporal precedence, i.e. the causal hierarchy between activities.