We consider the Bayes estimation of a multivariate sample selection model with p pairs of selection and outcome variables. Each of the variables may be discrete or continuous with a parametric marginal distribution, and their dependence structure is modeled through a Gaussian copula function. Markov chain Monte Carlo methods are used to simulate from the posterior distribution of interest. The ...

background : time to donating blood plays a major role in a regular donor to becoming continues one. the aim of this study was to determine the effective factors on the interval between the blood donations. methods : in a longitudinal study in 2008, 864 samples of first-time donors in shahrekord blood transfusion center,  capital city of chaharmahal and bakhtiari province, iran were selected by...

The presented work aims at tackling the problem of externally calibrating a network of cameras by observing a dynamic scene composed of pedestrians. It relies on the single assumption that human beings walk aligned with the gravity vector. Usual techniques to solve this problem involve using more assumptions such as a planar ground or assumptions about pedestrians’ motion. In this work, we drop...

Empirically oriented scholars often struggle with how to measure preferences across time and institutional contexts. This article characterizes these difficulties and provides a measurement approach that incorporates information that bridges time and institutions in a Bayesian Markov Chain Monte Carlo approach to ideal point measurement. The resulting preference estimates for presidents, senato...

Monitoring and Improving Markov Chain Monte Carlo Convergence by Partitioning by Douglas Nielsen VanDerwerken Department of Statistical Science Duke University

We merge in this note our two discussions about the Read Paper “Particle Markov chain Monte Carlo” (Andrieu, Doucet, and Holenstein, 2010) presented on October 16th 2009 at the Royal Statistical Society, appearing in the Journal of the Royal Statistical Society Series B. We also present a more detailed version of the ABC extension.