Sentence examples for in a multivariate setting from inspiring English sources

All these relationships and non-relationships hold in a multivariate setting controlling for the effects of other variables.

It was found that in a multivariate setting the relationship between mechanical and abrasion properties is stronger than the relationship between mechanical and hardness properties.

In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability.

The first objective is to examine the dynamic volatility and volatility transmission in a multivariate setting using the VAR(1)–GARCH(1,1) model for three major sectors, namely, Service, Banking and Industrial/or Insurance, in four Gulf Cooperation Council (GCC)'s economies (Kuwait, Qatar, Saudi Arabia and UAE).

In this section I analyze a firm's training participation in a multivariate setting.

The results of the experiment in a multivariate setting show that the Gaussian process regression model significantly improves the forecasting accuracy of a multi-layer perceptron neural network used as a benchmark.

Geometric quantiles are an extension of univariate quantiles in a multivariate set-up that uses the geometry of multivariate data clouds.

Hemoglobin did not add significantly to the prediction of superoxide dismutase in a multivariate set up (P = 0.229).

Multivariate mixed models enabled us to estimate the genetic covariance between expression traits in a variance-component form that has a standard interpretation for any pair in a multivariate set of quantitative traits and has well-known statistical properties (Lynch and Walsh 1998).

In the stepwise regression analysis for MDA, maternal albumin was found to be the most important predictor of lipid peroxidation in a multivariate set up (r = -0.885, SE = 0.171, F (1,38) = 136.6, P < 0.0001), followed by maternal hemoglobin (r = 0.925, SE = 0.586, F (2,37) = 109.577, P < 0.0001).

The Cox proportional hazards model was used to test the statistical significance of predictors in both a univariate and a multivariate setting.