Sentence examples for marginal computation from inspiring English sources

The marginal DNL algorithm that is presented, the Marginal Computation (MaC) algorithm, is based on first order kinematic wave theory.

This approximation has been obtained with the marginal computation (MaC) method that performs a perturbation analysis in a computationally efficient way, using the kinematic wave theory principles for traffic simulation.

The exact marginal likelihood computation is also more efficient than other computational approaches such as the Gibbs sampling (Zeger and Karim 1991; Burton et al. 1999), but for family data, it is still slow because of the high-dimensional integration (e.g., Pawitan et al. 2004).

The posterior probability of each model is estimated using the Chib Jeliazkov method that directly uses the posterior MCMC samples for evidence (marginal likelihood) computation.

sThe marginal effect computation and the conditional effect plots are based on a single-imputation approach as the estimation sample varies across imputations in the multiple imputation approach making it difficult to compute the AME.

Thus, the efficient computation of marginal genotype probabilities using equation 4 requires an efficient algorithm to compute the likelihood.

In other words, BP is a way of organizing the global computation of marginal beliefs in terms of smaller local computations.

The present paper is concerned with computation of marginal and joint reliability importance for a coherent system that consists of multiple types of dependent components.

In what follows we only review prominent techniques that have led to philosophical debate: Akaike's information criterion, the Bayesian information criterion, and furthermore the computation of marginal likelihoods and posterior model probabilities, both associated with Bayesian model selection.

This has favorable implications for both stability analysis, where small numerical errors in the energy may significantly affect the computation of marginal points, and transport applications, for which equilibrium computations on coarse meshes are desirable.

The belief propagation (BP) algorithm, proposed by Pearl [1], is a way of organizing the global computation of marginal beliefs in terms of smaller local computations within the graph.