The phrase "a set of posterior" is not correct in standard written English.
It may be intended to refer to a collection of posterior distributions in a statistical context, but it lacks clarity and specificity.
Example: "In Bayesian analysis, we often work with a set of posterior distributions to make inferences about the parameters."
Alternatives: "a collection of posterior distributions" or "a group of posterior results."
In a second step an algorithm for balancing errors was applied to produce a set of posterior maps that satisfied the water balance.
Brain activity was higher during place finding in RS than TSD participants in a set of posterior cortical areas including the left fusiform and lingual gyri, the right inferior parietal gyrus the right calcarine region, as well as the right middle and inferior occipital gyri (Table 3a).
The logistic regression based algorithm returns a set of posterior probabilities during the inference stage.
A set of posterior selection filters (see below) is then applied on these preliminary predictions to come up with a final prediction of the promoter region.
A set of posterior samples is produced as a by-product of nested sampling, and the first and second moments of parameters can be calculated from these samples.
The authors state: "MATS calculates a P-value for each exon isoform by comparing the observed posterior probability with a set of simulated posterior probabilities from the null hypothesis".
There is a need for including some learning mechanisms that can find the optimal mapping from a complete set of state activations to a set of state posteriors.
Once a set of anterior and posterior ROIs had been created, this set was applied to each whole-body scan of the ca I MIBG and nca I MIBG studies, including the transmission scans.
Assume that, at the observation time, we have a set of samples from the posterior,.
Application of the Bayesian framework to change point estimation provides a way of making a set of inferences based on posterior distributions for the time and the magnitude of a change as well as assessing the validity of underlying assumptions in the change point model itself (Gelman et al. 2004).
This results in a set of possible worlds from which posterior probabilities together with error bounds can be derived.
