Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop an algorithm for exact finite sample inference in this class time series models, commonly known as Proxy-SVARs. Our makes independent draws from any posterior distribution over parameterization a Proxy-SVAR. approach allows researchers simultaneously proxies and traditional ...

Bayesian networks have been applied for several uncertainty management problems in the artificial intelligence and Web intelligence communities. However, one may require the use of Bayesian networks, yet lack the background knowledge to build them. Moreover, it is widely acknowledged in the Bayesian network community that understanding Bayesian network inference is an arduous task. In this pape...

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...