Sentence examples for mixture modelling framework from inspiring English sources

Hernandez et al [ 22] compare linear and TOBIT models with adjusted censored models (which essentially modify the TOBIT) and similar models in a mixture modelling framework (but none were applied to cancer datasets and QLQ-C30 in particular).

Based on parametric and non-parametric mixture model framework, this paper classifies spectrum occupancy modelling approaches in literature based on predictor class selection.

Instead, they can be considered in a mixture model framework.

Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures.

Dynamic causal modelling (DCM) is a modelling framework used to describe causal interactions in dynamical systems.

We present a multiscale spatial modelling framework for transboundary invasions, incorporating robust modelling frameworks (Multimodel Inference and Ensemble Modelling) to overcome some of the limitations.

Methods include group-based trajectory modelling [10, 13] and growth mixture modelling (GMM) [11, 12].

Another possible modelling framework is to use generalized additive models (GAMs) rather than the parametric generalized linear models used in this study [47].

It is the flexibility of the modelling framework that makes it particularly useful for modelling EQ-5D values ([ 10]).

A mixture of normal models is employed and this features a couple of apparent advantages: (a) the modelling framework and methodology for the non-normal noise case depends only on a combination of already known and simple techniques for the normal case and (b) an easy economic interpretation could be put forward for the sudden changes in the behaviour of the process.

The main features of the model and the modelling framework are highlighted through two case studies: (a) the purification of a reaction mixture containing glycerol, mono-, di- and triglycerides, and (b) the recovery of a pharmaceutical product from a six-component mixture.