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We compare a sample-free method proposed byGargiuloet al.(2010) and a sample-based method proposed byYe et al.(2009) for generating a synthetic population, organised in households, from various statis...
Bayesian methods - either based on Bayes Factors or BIC - are now widely used for model selection. One property that might reasonably be demanded of any model selection method is that if a modelM1 is...
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The social web forms an excellent modern paradigm, where unstructured user generated content is pu...
In this paper, we propose new sequential estimation methodsbased on inclusion principle. The main idea is to reformulate the estimation problems as constructing sequential random intervals and use con...
Many biological characteristics of evolutionary inter-est are not scalar variables but continuous functions.Here we use phylogenetic Gaussian process regres-sion to model the evolution of simulated fu...
In this paper, we consider the classic measurement error regression scenario in which our independent,or design, variables are observed with several sources of additive noise. We will show that our mo...
The following zero-sum game between nature and a statistician blends Bayesian methods with frequentist methods such as p-values and confidence intervals. Nature chooses a posterior distribution consis...
We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity o...
Adaptive treatment allocation schemes based on interim responses have generated a great deal of recent interest in clinical trials and other follow-up studies.
The problem of prediction in functional linear regression is conventionally addressed by reducing dimension via the standard principal component basis. In this paper we show that weighted least-square...

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