These beliefs are updated via Bayes' Theorem to obtain a posterior probability distribution
for the model parameters that quantifies our beliefs refined after incorporating the [sup.
The basis for the Bayesian analysis of reporting period savings is the joint posterior probability distribution
for the baseline regression parameter vector E and the variance [[sigma.
For AT1 transients, in contrast, there was a distinct peak in the posterior probability distribution
for a change-point, and 97% of the posterior density for an abundance change occurred in the five years after 1989.
The 95% confidence interval of posterior probability distribution
of the reaction rate constant includes the parameter estimate derived by the initial reaction rate method.
In this general case, the agnostic approach implies that each policy intervention (each [DELTA]) leads to a set of posterior probability distributions
These graphs also serve a diagnostic function as the suitability of the convergence (behavior of the curves) may be assessed, The sample monitoring tool offers several other very useful diagnostics including trace, history, autocorrelation and kernel density curves, as well as the actual statistical outputs of the parameters and quantiles (Credible Intervals in Bayesian parlance) around them These outputs constitute the estimates of the posterior probability distributions
, which may be further utilized in statistical inference.