Sentence examples for likelihood of observation from inspiring English sources

The HGS-FIR filter adjusts horizon size based on the likelihood of observation and achieves a significant performance improvement.

The strategy was to maximize the likelihood of observation.

The utility of carcasses for case detection depends on the likelihood of observation and subsequent reporting (3 ).

Such methods are typically referred to as enhanced sampling techniques because they increase the likelihood of observation of a rare biomolecular event.

Additional reliable PHP data (and, ideally, a refined estimation of position-specific rates) will be needed to clarify the relationship between the likelihood of observation of heteroplasmy in relation to mutation and substitution rates in the coding region, and to determine whether any true heteroplasmic hotspots exist in the coding region.

Because the probability of measurement error at time t + 1 will be included in the next term in the product when we factor in the likelihood of observation y t+2 conditioned on y t+1 —we can simply view f as describing process variation.

The problem of detecting dangerous situations then becomes a classification problem, where the likelihood of observations is used to select the model which best explains the current observations.

Beliefs posterior to observing the world, including the self, need not accord with the maximum likelihood of observations: other constrains enter inference too, as we have seen in some detail.

Moreover, censored observations of hCG titres below the limit of quantification (i.e., those measurements recorded as <2 IU l−1) were handled using the so-called M3 method, which considers the likelihood of observations being below the quantifiable limit (Beal, 2001; Ahn et al, 2008; Bergstrand and Karlsson, 2009).

Again, using the independence of the observations the likelihood of the observation vector y k conditioned on x k can be factorized as p ( y k | x k ) = p ( y k ( t i − 1 ), y k ( t i ) | x k ) ∏ m ∉ { i − 1, i } p 0 ( y k ( t m ) ), (14).

where J is a P × P matrix, f is the likelihood function of observation vector Λ, and E represents the expectation operation.