A hierarchical Bayesian model for spatial panel data is proposed. The idea behind the proposed method is to analyze spatially dependent panel data by means of a separable covariance matrix. Let us indicate the observations as yit, i = 1, ... ,N regions and t = 1,... , T time, var(y), the...

A hierarchical Bayesian model for spatial panel data is proposed. The idea behind the proposed method is to analyze spatially dependent panel data by means of a separable covariance matrix. Let us indicate the observations as yit, i = 1,...,N regions and t = 1,...,T time, var(y), the covariance...

We propose a Bayesian model for physiologically based pharmacokinetics of 1,3-butadiene (BD). BD is classified as a suspected human carcinogen and exposure to it is common, especially through cigarette smoke as well as in urban settings. The main aim of the methodology and analysis that are...

Based on reinforced urn process introduced by Muliere et al. [2000. Urn schemes and reinforced random walks. Stochastic Process. Appl. 88(1), 59-78] we propose a Bayesian nonparametric approach to analyse a design determining the maximum tolerated dose (MTD) in Phase I clinical trials for new...