Sentence examples for model constraining the from inspiring English sources

For each locus, we generated an expected distribution of likelihood differences as follows: using Phylobayes 3.3f (ref. 48), we first used the 'pb' MCMC sampler to obtain the posterior distribution of substitution model parameters under the CAT GTR model, constraining the topology to the species (H0) tree.

We utilize layer-based raytracing in a Markov Chain Monte Carlo (MCMC) inversion to determine a probabilistic velocity model constraining the sedimentary rocks, crystalline crust, and uppermost mantle in a complex tectonic regime.

The first model, constraining the MRCA of both subfamilies into the Middle Eocene (45 Ma), i.e., before the final Indian-Eurasian collision, is superior to all other models.

As Figure 2 shows, the model constraining the loadings across the groups has solid black lines from the latent variable (solid circle) to the latent response variates, indicating that the loadings have been constrained to equality.

A second MGCFA model constraining the factor loadings to be the same in the two age groups resulted in a significantly larger χ² value (χ² = 2288.1 df = 929 P < .001; Δχ² = 108.3 df = 25 P < .001) with a moderately larger RMSEA = .071 and the same CFI = .94 (ΔCFI = .00).00

Three models of molecular evolution were compared: 1) the one-ratio model (model = 0), allowing the same d N/d S value for all branches; 2) the two-ratio model, constraining the branches within the cichlid clade to one d N/d S ratio that was different from all the others (model = 2); and 3) the free-ratio model (model = 1), allowing one d N/d S ratio per each branch.

The model constrains the momentary wastewater (WW) velocity in the sewer pipes (which is responsible for solids movement).

The models are mathematically equal, however, the Rasch Model constrains the Item Discrimination (ai) to 1, while the 1-Parameter logistic model strives to fit the data as much as possible and does not limit the discrimination factor to 1.

The lack of a macroscopic gas channel (GC) flooding model constrains the current predictions of PEFC modeling under severe flooding situations.

These approaches permit the direct prediction of head pose when an inherent 3D model constrains the fitting of 2D points.

The probit model constrains the probability to (0, 1) interval and assumes that the probability that an event will occur is non-linear and that the random error terms follow a normal distribution.