Sentence examples for maximum posterior density from inspiring English sources

These results are shown in Table 5. Figure S4 shows 95% credible intervals with maximum posterior density for the estimated parameter values.

Once the posterior probability density function is obtained, a minimum mean square error estimation and maximum posterior probability density estimation can be accomplished by compute mean and mode, respectively.

The MAP estimation is based on finding the maximum of the posterior density rather than the whole posterior distribution, usually by an expectation-maximization (EM) algorithm (Dempster et al. 1977; McLachlan and Krishnan 1997).

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].

'High' migration models used the maximum of the 90% posterior density intervals: 17.71 L. a. astyanax to L. a. arthemis and 15.53 L. a. arthemis to L. a. astyanax.

In cases of significant differences we calculated Bayesian maximum posterior estimates as well as highest posterior density intervals with 95% support (HPDI95%) for the interaction effects.

The procedure conforms to an EM implementation of a Gauss Newton search for the maximum of the conditional or posterior density.

Posterior probability distributions for all parameter estimates and datasets are presented in Figure 2 and HiPt (Maximum likelihood) and 90% highest posterior density boundaries in Table 2. Ne = effective population size.

After the data have been collected, the (asymptotic) sampling variance of the estimate can be derived from the analysis, for example, from mean squares in balanced designs, from the information matrix when using maximum likelihood or from the posterior density in Bayesian analysis.

Most probable trees were selected based on three methods; approximate likelihood-ratio test (aLRT) statistics [ 39] implemented in PhyML and combination of 9 statistical analysis implemented in CONSEL [ 40] in the maximum-likelihood methods, and 95% highest posterior density (HPD) in Bayesian MCMC.

Asterisks indicate posterior density intervals that exceed maximum priors for the parameter.