Sentence examples for multiple response regression from inspiring English sources

Here, a method for inverting contaminant transport models is presented including a general error model and procedures for differentially weighted multiple response regression.

Summary: ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression.

Experimental planning, regression and multiple response analysis were used in data processing and to optimize the drying conditions.

For problems with multiple response variables available, one common approach is to apply the univariate response regression technique separately on each response variable.

Thus, for this categorical variable with multiple responses, a cumulative logistic regression model was used to model odds of being more confident to less confident.

This approach is based on regression modelling with multiple responses and a rotation testing analysis was therefore performed for each column in Tables 2, 3, 4 and 5.

Maronna et al. (2006) proposed many M-estimators using robust regression methods in both single response and multiple responses.

Response probability was assessed by a multiple logistic regression with response as dependent variable (yes/no) and eight demographic and practice related variables as predictors.

In multiple linear regression, the response variable is modeled as a linear combination of multiple predictor variables.

Second-order polynomial models with high R2 values ranging from 0.945 to 0.977 were developed for the studied responses using multiple linear regression analysis.

A complete strategy dedicated to quality-by-design (QbD) compliant method development using design of experiments (DOE), multiple linear regressions responses modelling and Monte Carlo simulations for error propagation was evaluated for liquid chromatography (LC).