Large-Sample Bayesian Posterior Distributions for Probabilistic Sensitivity Analysis

Large-sample Bayesian posterior distributions for probabilistic sensitivity analysis.

In probabilistic sensitivity analyses, analysts assign probability distributions to uncertain model parameters and use Monte Carlo simulation to estimate the sensitivity of model results to parameter uncertainty. The authors present Bayesian methods for constructing large-sample approximate posterior distributions for probabilities, rates, and relative effect parameters, for both controlled and...

Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions

W a decision analyst desires a sensitivity analysis on model parameters that are estimated from data, a natural approach is to vary each parameter within one or two standard errors of its estimate. This approach can be problematic if parameter estimates are correlated or if model structure does not permit obvious standard error estimates. Both of these difficulties can occur when the analysis o...

1 2 Large - Sample Bayesian Posterior Distributions for 3 Probabilistic Sensitivity Analysis

Probabilistic sensitivity analysis: be a Bayesian.

OBJECTIVE To give guidance in defining probability distributions for model inputs in probabilistic sensitivity analysis (PSA) from a full Bayesian perspective. METHODS A common approach to defining probability distributions for model inputs in PSA on the basis of input-related data is to use the likelihood of the data on an appropriate scale as the foundation for the distribution around the i...

Quantitative Comparisons between Finitary Posterior Distributions and Bayesian Posterior Distributions

Abstract. The main object of Bayesian statistical inference is the determination of posterior distributions. Sometimes these laws are given for quantities devoid of empirical value. This serious drawback vanishes when one confines oneself to considering a finite horizon framework. However, assuming infinite exchangeability gives rise to fairly tractable a posteriori quantities, which is very at...