Sentence examples for likelihood to form from inspiring English sources

Classical clustering techniques are used to determine groups of pixels, as well as their likelihood to form a single object.

Melts whose (O/Na), (Na/P) or (Na/Al) molar ratios were ≤ 4.35, ≥ 1.13, or ≥ 2.56, respectively, had the highest likelihood to form glass when cooled.

However, the addition of more Fe and Ta β-stabilizers to Ti 8Fe alloy reduced the likelihood to form α″ martensite during quenching, hence decreasing the volume fraction of α″ phase and finally reaching 3% in Ti 10Fe 10Ta alloy.

Few factors have been proposed to influence a domain's likelihood to form many combinations.

In addition, the A30P mutation appears to affect αS independently of protein aggregation, probably by partially impairing the ability of αS to bind to brain vesicles, likely due to a decreased likelihood to form α-helices [ 30, 52].

Briefly, these methods break up the dataset into smaller subsets (pairs or triplets of segregating sites), compute the likelihoods (as functions of ρ and γ, with λ fixed) for the subsets, and then multiply those likelihoods together to form a composite likelihood.

For example, spatial proximity of chromatin segments [ 11], which in some regions is regimented [ 12, 13], has been observed to increases the likelihood of interaction to form a new structural variation [ 13].

The CCREL method permits testing for association with the use of related cases and unrelated controls simultaneously and, briefly, it accounts for biologically related subjects by calculating an effective number of cases such that individuals are assigned weights that are used to construct a composite likelihood, which is then maximized iteratively to form likelihood ratio tests.

Move increases the likelihood of an agreement to form a unity government.

The list sphere detector (LSD) [14, 15] is an efficient method to conduct an exhaustive search among a set of candidates (i.e., ML detection) producing not only the most likely estimate but also a list with the closest candidates, which can then be used to form likelihood ratios (LLRs) for each bit (i.e., soft information).

Type 3 equivalent sums of squares from the model were used to form likelihood ratio tests of model effects and various tests of hypotheses.