Sentence examples for marginal convergence from inspiring English sources

This article reviews the biomechanical basis of rotator cuff tear and repair, and surgical technique of rotator cuff repair, outcome of arthroscopic rotator cuff repair, and important considerations in rotator cuff repair, including tear pattern recognition, marginal convergence, and suture technique.

Several (mathematical) details of the procedure, such as approximate equivalence to maximum marginal likelihood, convergence criteria and various types of parametric priors are further discussed in [ 3].

The results related to the convergence of marginal functions and approximated solutions were given and the case of data perturbations was also considered.

The objectives of this study were to identify the effect of design parameters, namely marginal thickness, degree of convergence and the different interfacial conditions, on the initial failure load that induces cracking from the margin in glass-simulated dental crowns.

Convergence of marginal POR model seems much better than non-linear mixed model, when fitted to cell counts of incomplete matched groups.

Searching databases using the yeast TAF25 sequence as a probe led to the identification by convergence of marginal similarities with the P. falciparum PFE1110w hypothetical protein (E-value 1.5; 25% sequence identity over 52 amino acids).

We have ρ (H3) < ρ (H2) for a > ( - 1 + 6 ) / 2. For certain marginals, the rate of convergence of Theorem 3 ii) can be determined (Lin and Huang 2011 and Theorem 4 below).

Bayesian results were comparable to maximum likehood method but they avoided convergence problems, the marginal likelihood allowed to compare all models, and credible interval gave directly the uncertainty of sorption parameters θ.

But in this example, this effect is corrected by the rapid convergence of the marginal distribution toward the stationary distribution ensured by a very low second magnitude eigenvalue of the matrix: μ = 0.049.

Unfortunately, we have seen in our applications that this approach is subject to important edge effects, especially when the convergence of the marginal distribution of the model toward the stationary distribution is slow.

Here, we use L-BFGS to maximize the marginal likelihood due to its fast convergence and low-memory consumption.