Sentence examples for posterior computation from inspiring English sources
We implement the Integrated Nested Laplace Approximation (INLA) approach to enable fast Bayesian posterior computation.
A Gibbs sampling algorithm based on adaptive rejection sampling is designed for the posterior computation.
Multilevel-specific obstacles to Bayesian posterior computation via Markov chain Monte Carlo are discussed.
In addition, a lack of simple and efficient algorithms for posterior computation has made more elaborate hierarchical Bayesian approaches appear unattractive in the context of software defect prediction.
The Gibbs sampler is developed for posterior computation.
Hamiltonian Monte Carlo has emerged as a standard tool for posterior computation.
Since the combination step takes negligible time relative to sampling, posterior computations can be scaled to massive data by dividing the full data into sufficiently large number of data subsets.
(PDF 81.7 kb) Additional file 3: Posterior computations through Gibbs sampling.
Prior and posterior probability computation of the scRNA-seq data.
From the posterior distribution, computation of estimates and standard errors is immediate.
This test process is repeated for each cost function associated to each posterior probability computation strategy: P boost, P knn, and P comb.
