Agostino Nobile

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A new Markov chain Monte Carlo method for the Bayesian analysis of finite mixture distributions with an unknown number of components is presented. The sampler is characterized by a state space consisting only of the number of components and the latent allocation variables. Its main advantage is that it can be used, with minimal changes, for mixtures of(More)
Dual-channel microarray experiments can be regarded as designs with block-size two. Our aim is to find D-optimal, A-optimal and related L-optimal designs for such experiments. Previous work has focussed on exhaustive search algorithms, which in many practical, large-scale experiments is infeasible. We propose using simulated annealing to search for(More)
The number of cars in a household has an important eeect on its travel behavior (e.g., choice of number of trips, mode to work, and non-work destinations), hence car ownership modeling is an essential component of any travel demand forecasting eeort. In this paper we report on a random eeects multinomial probit model of car ownership level, estimated using(More)
We give an overview of the QPACE project, which is pursuing the development of a massively parallel, scalable supercomputer for LQCD. The machine is a three-dimensional torus of identical processing nodes, based on the PowerXCell 8i processor. The nodes are connected by an FPGA-based, application-optimized network processor attached to the PowerXCell 8i(More)
The posterior distribution of the number of components k in a finite mixture satisfies a set of inequality constraints. The result holds irrespective of the parametric form of the mixture components and under assumptions on the prior distribution weaker than those routinely made in the literature on Bayesian analysis of finite mixtures. The inequality(More)
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