Sentence examples for components of multivariate from inspiring English sources

This method quantifies the covariation of components of multivariate longitudinal data.

Independent component analysis (ICA), one of the multiple-regression methods, is a robust technique based on blind source separation that captures the essential components of multivariate rs-fMRI signals [ 13].

Adjusted and unadjusted analyses were considered separately, as well as exploration of the impact of different components of multivariate adjustment (age and sex, disease severity, disease duration, comorbidity, and other RA therapies).

In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits.

The eigenvalue of the first component of multivariate analysis was 3.56, accounting for 19% of the total variability in the dataset.

PCA is a popular technique used to find the major component of multivariate data, in DNA microarray analyses, it is used to find the gene groups that cooperatively change expressions over several experiments (Brunet et al., 2004), where PCA is done in gene space.

The concept of seemingly unrelated models is used for multivariate observations when the components of the multivariate dependent variable are governed by mutually different sets of explanatory variables and the only relation between the components is given by a fixed covariance within the observational units.

Currently, the standard approach is to model wind velocities as discrete components of a multivariate stochastic vector process, characterized by a Cross-Spectral Density Matrix.

In this paper, we propose an approach to identify the components of a multivariate disease phenotype that maximizes the chip h.

Because all metabolic components of the multivariate model are obtained during the fasting state, these models have been proposed to replace the diagnosis of IGT in identifying subjects at increased risk for future type 2 diabetes, thereby obviating the need to perform an OGTT.

Two techniques, Change Vector Analysis (CVA) and Maximum Autocorrelation Factor transform of Multivariate Alteration Detector components (MAD/MAF) are chosen to serve the purpose.