Sentence examples for data-driven multivariate analysis from inspiring English sources
We used a data-driven multivariate analysis to capture the dominant group- and task-related trends in information generation across a network of MEG sources.
ICA is a data-driven multivariate analysis method that can be used to separate any multivariate signal into subcomponents that are mutually statistically independent.
The dominant methodologies can be segregated into region of interest-based or seed-based correlation studies and data-driven multivariate analysis techniques, such as independent component analysis (ICA), and are described in detail here.
Non-parametric data reduction methods, on the other hand, include data-driven multivariate component analysis such as the application of matrix factorization methods to time-frequency distributions.
To confirm and extend our observations we carried out a data-driven, multivariate statistical analysis to determine the genomic feature(s) that best explain the variation in gene expression in response to iXist-mediated silencing.
The two networks extracted in this work could be compared to those commonly extracted by many groups in the decomposition of fMRI/PET resting state signals, using blind data-driven multivariate techniques as principal component analysis, independent component analysis, subprofile scaling model, fuzzy clustering [35, 39, 40].
Benjamins, J. S. et al. Insomnia heterogeneity: characteristics to consider for data-driven multivariate subtyping.
Hypothesis-driven multivariate analysis using ANCOVA was undertaken to assess the following hypothesis: Muscle atrophy does progress with age.
While Ishikawa aims to bring clarity about analytical techniques for SBD (for example, modeling, data mining, multivariate analysis), Pentland envisions a data-driven society.
The increasing number of publications focused on multivariate and data-driven analysis of brain network dynamics is a clear indication that researchers embrace this challenge, on both a conceptual and a methodological level.
Figure 6 compares the embedded mobile node tracking position error of hydraulic analysis algorithm with crowd lightweight data-driven algorithm (HA-CLDD) and hydraulic analysis algorithm with data-driven (HA-DD) based on lightweight crowd data-driven hydraulic analysis.
