Sentence examples for likelihood information from inspiring English sources

To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors.

The absence of event and likelihood information renders futile the application of usual risk-based methods for design.

The result is obtained by iteratively fusion of the pixel likelihood information and the pixel contextual information until convergence.

A partial information matrix is built in this case and optimal designs are computed and compared with the optimal designs for the full likelihood information.

Our approach involves the design of special overcomplete dictionaries that match the structure of the likelihoods and the transmission of likelihood information in the network through sparse representation in such dictionaries.

This method makes use of the conception of Markov random fields (MRFs) and D S evidence theory to obtain segmentation results by considering both likelihood information and priori information under Bayesian framework.

To account for possible over-dispersion in mark-recapture data, the model selection was based on a quasi-likelihood information criterion.

A goodness-of-fit statistic, quasi-likelihood information criterion (QIC) for data correlated models will be used for evaluating GEE-constructed models.

For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures.

The final model was selected using a quasi-likelihood information criterion (QIC) approach.

Briefly, a full model is simplified until a minimum quasi-likelihood information criterion is obtained.