Sentence examples for mixture regression model from inspiring English sources

Based on simplex algorithm of optimal design, the multicomponent mixture regression model was used to investigate physical properties of submerged arc welding flux.

The case of a two finite step distribution, the finite Poison mixture regression model of Wang et al.'s ([1996]) results.

The resulting expression for the regression weights is

In this article, we propose a discrete mixture regression model that synergizes with potential heterogeneity in time-to-event data.

Obstetric complications of large for gestational age births were then determined by including the complication variables into the final estimated hierarchical mixture regression model via logistic regression.

Following data preprocessing, the algorithm classifies genomic regions as background, enriched or zero-inflated using a mixture regression model, without a priori knowledge of genomic enrichment.

This study investigates via simulation the performance of seven segment retention criteria used with finite mixture regression models for normal data.

This is one of the most important analysis contexts in marketing research since regression models are used, for example, in conjoint analysis and market response analysis, yet no previous study in either the marketing or statistics literatures explores the segment retention problem for mixture regression models.

In this article, we propose marginalized mixture regression models based on two-component mixtures of non-degenerate count data distributions that provide directly interpretable estimates of exposure effects on the overall population mean of a count outcome.

"Methods and Results" section reviews traditional and marginalized zero-inflated count regression models, while "Models for mixtures of non-degenerate count distributions" section discusses traditional finite mixture regression models and proposes marginalized two-component count regression models involving mixtures of non-degenerate distributions.

Despite the flexibility of finite mixtures for describing highly dispersed count data, parameters from standard mixture regression models are not directly applicable to making inferences about the overall effects of covariates on marginal means of count outcomes (Albert et al. 2014; Preisser et al. 2012).