Sentence examples for variability of assumptions from inspiring English sources

Another problem for quantitative comparison among different studies is the variability of assumptions made in different models.

A philosophical rôle of CL is to show the variability of the ontological assumptions a theory has.

The chance of an outbreak with >100 transmissions is negligible (<0.01%) for k = 10 and k = 1 but rises to ≈0.4% under a high variability assumption of k = 0.1 because of increased likelihood of superspreading.

The contrary assumption, variability of biological process, suggests that one cannot isolate interactions between two transgenic products from interactions of each transgenic product with domestic proteins.

Mutual information quantifies odor discriminability taking into account not only the separation of mean neural responses but also the variability of responses without any assumption of specific decoders.

The unbiasedness of these procedures and the controls of the variability of the estimates require moments assumptions and Holder type conditions on the parameters of the SDE (1).

Essentially, codon models fit a set of Markov models to the observed data (here: the extant sequences and the phylogenetic tree) and calculate a likelihood function under different assumptions regarding variability of dN /d S across different sites of the protein, branches of the phylogeny, or both (Yang 2006).

This premise is the alternative assumption of variability of biological process, which implies separating the methodological similarity from any claims of biological equivalence.

This study tests the assumption that variability of δ18O ratios of water from within a region are insufficient to impact the reconstruction of ancient mobility using isotopic measures of human tooth and bone.

This set of assumptions has also been made when inferring functional variability from phylogenetic tree distances between OR genes based on the entire protein sequence (e.g., [14]).

We developed two different analytic models by varying the underlying statistical assumptions regarding the variability of the clinical treatment centers, i.e., random or fixed effects.