This study proposes to investigate the effectiveness of modeling local spatial dependence through a conditionally autoregressive process (CAR) to picture the population distribution across space. Following the current literature, the idea is to model individual location preferences by focusing...

This study aims to investigate the extent to which history matters in shaping population distribution across space. In the wake of the current literature, the idea is to model individual location preferences by focusing on selected local determinants (neighborhood, education, income, amenities...

The definition of vectors of dependent random probability measures is a topic of interest in applications to Bayesian statistics. They, indeed, represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. In this...

In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently it has been shown that they can also be exploited in species sampling...

Move-to-front rule is a heuristic updating a list of n items according to requests. Items are required with unknown probabilities (or ppopularities). The induced Markov chain is known to be ergodic [4]. One main problem is the study of the distribution of the search cost defined as the position...