Sentence examples for models with principal from inspiring English sources

For each colony and immune measure we fit generalised linear models with principal components that explained ≥ 5%% of the variation as response variables to homozygosity weighted by locus (HL) [ 52], sex and their interaction as explanatory terms, removing interactions if they were non-significant [ 71].

Average accuracy was 97.6% for action detection using Gaussian Mixture Model with Principal Components Analysis and 96.7% for activity recognition.

The damage initiation and propagation in resin are simulated by the post-damage constitutive models with maximum principal theory failure criteria.

Various studies have employed Cox models with the principal aim of determining the risk factors for the progression of cirrhosis to HCC [ 24, 25].

Fixed additive and dominance effects of casein haplotypes were estimated using single trait mixed model combined with principal component analysis (PCA) to solve multicolinearity in the design matrix.

Consequently, molecular modeling coupled with principal component analysis seems to be a unique, inexpensive, and rapid tool to select the appropriate hapten providing highly specific or class-specific antibodies according to the given problem.

Mixture models are built with Principal Components Regression (PCR) and Partial Least Squares Regression (PLS) which are adequate for systems with incomplete or redundant information, because the informativity of the data with respect to the models is not guaranteed.

Based on continuum damage mechanics, a Principal Damage Model is developed by combining the generalized standard material model with the Principal Damage concept of composite materials.

A theoretical elastic rectilinear orthotropic model with three principal directions of elasticity: longitudinal (L), radial (R), and tangential (T) has been adopted in development of this study.

Experimental results were approximated to a second-order model with the principal effects of the three factors considered being statistically significant (P < 0.05).

In this paper we analyze an adverse selection model with one principal and one agent, who are both risk neutral and have private information.