Sentence examples for estimation of regression from inspiring English sources

We outline a specific mean value structure adapted to model seasonal variation of hospitalizations with stroke in patients with AF and propose an algorithm to estimate variance parameters and outline estimation of regression estimates and calculation of model diagnostics.

'Using M-estimators for robust estimation of regression coefficients' section presents the robust M-estimator procedure and the modification of the response surface by an iterative weighting procedure.

A Bootstrap replication method was used that made appropriate use of these longitudinal bootstrap weights for the variance estimation of regression estimates.

Estimation of regression functions from independent and identically distributed data is considered.

This paper studies nonparametric estimation of regression quantiles under the fixed design model.

A good feature space coverage ensures accurate estimation of regression parameters, while spatial coverage contributes to effective spatial interpolation.

Many analyses in labor economics, and in the social sciences more generally, entail estimation of regressions in which "cognitive ability" θ i appears as an explanatory variable.

Multivariate regression analyses comprised the following working steps [27]: Setting the framework for the regression model, estimation of the regression function, verification of the regression function and coefficients as well as verification of the underlying assumptions of the regression model.

To further improve the performance of the regression-based methods, we propose shrinkage regression-based methods which use a shrinkage estimator to replace the least square estimator for the estimation of the regression coefficients in the regression model.

When p ≫ 1, the Cox regression model is prone to noise and tends to produce unreliable estimations of regression coefficients.

Over-dispersion is a common problem and leads to inaccurate estimations of regression coefficient standard errors that can influence the precision of the hypothesis test results.