In this paper we develop a dynamic data-consistent way for estimating agricultural land use choices at a disaggregate level (district-level), using more aggregate data (regional-level). The disaggregation procedure requires two steps. The first step consists in specifying and estimating a...

In this paper, a Bayesian procedure is implemented for the Probability Tsunami Hazard Assessment (PTHA). The approach is general and modular incorporating all significant information relevant for the hazard assessment, such as theoretical and empirical background, analytical or numerical models,...

Many economics and finance time series are non-Gaussian. In this paper, we propose a Bayesian approach to non-Gaussian autoregressive time series models via quantile functions. This approach is parametric, so we also compare the proposed parametric approach with a semi-parametric approach....

This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson purchase process, (2) a memoryless dropout...

We present a statistical model for voter choice that incorporates a consideration set stage and final vote intention stage. The first stage involves a multivariate probit model for the vector of probabilities that a candidate or a party gets considered. The second stage of the model is a...

We present a statistical model for voter choice that incorporates a consideration set stage and final vote intention stage. The first stage involves a multivariate probit model for the vector of probabilities that a candidate or a party gets considered. The second stage of the model is a...