Sentence examples for models to decompose from inspiring English sources

We adopt both the refined Laspeyres and the Logarithmic Mean Divisia Index models to decompose the driving forces of industrial water use.

Supporting internal program models to decompose the geometric model representation into appropriate intrinsic and extrinsic states, they need to adopt the concept of scene graphs.

For each of the nine data sets, we used mixed Gaussian models to decompose the density of ESR1 expression into two normal distributions and then derived a dataset-specific, optimal threshold value by Mahalanobis distance-based discrimination (Supplement Figure S2 showing the distribution of ESR1 levels for the DFCI cohort, other data not shown).

We used linear mixed models to decompose the variance of the composites into two components: the FP level and the country level.

Importantly, because many but not all risk factors will directly influence neuropathology, this will entail careful mediation models to decompose direct, indirect, and interactive pathways.

We use a simple model to decompose the relative contribution of technology and regulation to the rise of shadow banks.

RDF uses an abstract model to decompose information into small pieces with well-defined semantics (meaning), so as to express knowledge in a general, yet simple and flexible way.

The fourth equation uses the conditional independence encoded in our graphical model to decompose the probability to products of different features.

The key innovations of SPEDRE are the use of a probabilistic graphical model to decompose the dual objective function, and pre-computation of discrete solutions to each sub-problem.

Thus far we have shown that the ability of the two species model to decompose key Raman bands into separate contributions from morphology-dependent PBTTT conformers offers a much simpler means to assess order/disorder transitions in this system.

Even remotely related pairs of individuals are excluded so that chance genetic similarity is used as a random effect in a mixed linear maximum likelihood model to decompose phenotypic variance into genetic variance as captured by the additive effects of causal variants in linkage disequilibrium with SNPs genotyped on DNA arrays (Yang et al. 2011b).