Dec 1, 2006 · This approach can be problematic if parameter estimates are correlated or if model structure does not permit obvious standard error estimates.
Hazen and Huang: Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions. Decision Analysis 3(4), pp. 208–219, © 2006 ...
"Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions," Decision Analysis, INFORMS, vol. 3(4), pages 208-219 ...
Dive into the research topics of 'Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions'. Together they form a unique ...
A large-sample approximate multivariate normal Bayesian posterior distribution can be fruitfully used to guide either a traditional threshold proximity ...
[PDF] Large-Sample Bayesian Posterior Distributions for ...
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Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions · Gordon B. HazenMin Huang. Mathematics, Business · 2006.
Background Probabilistic sensitivity analyses (PSA) may lead policymakers to take nonoptimal actions due to misestimates of decision uncertainty caused by ...
A Bayesian Decision-Theoretic Dose-Finding Trial · Abstract · Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions.
▻ Conduct formal sensitivity analysis with respect to that class: See whether the parametric conclusions rely on the specification of those suspect ...
Dec 10, 2019 · Bayesian analysis of Dillon et al. (2013)'s Experiment 1. The table shows the mean of all fixed effects' posterior distributions together with ...