Sentence examples for mixed parametric from inspiring English sources

Based on the level-cut technique, a first-order fuzzy interval perturbation FE/SEA (FFIPFE/SEA) and a second-order fuzzy interval perturbation FE/SEA method (SFIPFE/SEA) are developed to handle the mixed parametric uncertainties efficiently.

Pearson's, Spearman's, and two-way mixed parametric intraclass correlation coefficients were used to estimate the association of the scores obtained in both ways.

The comparison of the two scoring alternatives was also performed through a paired design involving weighted and unweighted scores: Spearman's, Pearson's (r) and two-way mixed parametric intraclass (ICC) correlation coefficients were used to estimate the association of the scores obtained in both ways.

The 300 digital HR data were also analyzed with parametric (mixed ANOVAs) and non parametric (Chi-Square and Mann-Whitney U test) statistics with Statistica 8 software.

Currently, methodology for fitting parametric mixed effect models for VLDSs is underdeveloped.

Our algorithm works by choosing an appropriate finite sequence of non-parametric mixed integer linear programming (MILP) problems in order to obtain a complete multiparametrical analysis.

For trapezoidal and normal fuzzy travel times, we first turn the original VaR p-hub center problem into its equivalent parametric mixed-integer programming problem, then develop a hybrid algorithm by incorporating genetic algorithm and local search (GALS) to solve the parametric mixed-integer programming problem.

To solve the fuzzy bi-objective H&S network design problem, we develop a two-phase approach, where in the first phase we convert the proposed model into its equivalent parametric mixed-integer programming problems by applying an equivalent transformation method.

Table  2 shows results from both standard logistic regression models (unadjusted and adjusted) and the geo-additive semi-parametric mixed model for only young women of reproductive age.

Table  1 shows results from both standard logistic regression models (unadjusted and adjusted) and the geo-additive semi-parametric mixed model for all women of reproductive age.

In the following section, we evaluate our training population design scheme by fitting a semi-parametric mixed model (SPMM) [ 23, 24] using the genotypes and phenotypes in the training set and calculating the correlation of the test set phenotypes to their predictions based on this model.