Hence, if the selected model included interaction effects, the model was again fit with MCMCglmm to obtain Bayesian maximum posterior estimates and highest posterior density intervals with 95% support (HPDI95%) for parameter estimates of interaction effects [93].
This article discusses a new approach to map accuracy assessment based on maximum posterior probability estimators.
The test point is classified by the maximum posterior probability.
After all, assuming unimodality of the posterior function, one can get the optimal maximum posterior solution for the maximum likelihood estimate.
Each box is centered at the posterior mean, extends one posterior standard deviation away, and the bottom and top notches are the minimum and maximum posterior samples, respectively.
The tissue pixel is classified into one class where it attains the maximum posterior probability.
The replays were ordered by the location showing the maximum posterior probability.
Regions are classified into the mixture components (clusters) using the maximum posterior allocation rule.
We plot the maximum posterior probability for each patient by their survival time in Figure 3A.
Genes were classified based on the maximum posterior probability (Supplementary file 3).
