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Big data problems present great challenges to statisti-cal analyses, especially from the computational side. In this paper, we consider regression estimation of high-order mo-ments in big data problem...
In this paper, we consider the problem of modelling historical data on retail credit portfolio performance, with a view to forecasting future performance, and facilitating strategic decision making. W...
This paper aims to enhance our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multi-level models. To date, there have bee...
Computer model evaluation studies build statistical models of deterministic simulation-based predictions of field data to then assess and criticize the computer model and suggest refinemen...
We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point proces...
This paper illustrates a novel hierarchical dynamic Bayesian network modelling the spiking patterns of neuronal ensembles over time. We introduce, at separate model stages, the parameters characteri...
Intheconjugate priorforthenormallinear model, theprior variancefor the coecients is a multiple of the error variance parameter. However, if the prior mean for the coecients is poorly chosen, the pos...
Bayesian robustness modelling using heavy-tailed distributions pro- vides a exible approach to resolving problems of conicts between the data and prior distributions. See Dawid (1973) and OHaga (197...
Spatial Modelling of the Relative Risk of Dengue Fever in Rio de Janeiro for the Epidemic Period Between 2001 and 2002。
Modelling Game Outcomes of the Brazilian 2006 Series A Championship as Ordinal-valued。
The measured properties of stellar oscillations can provide powerful constraints on the internal structure and composition of stars. To begin this process, oscillation frequencies must be extracted ...
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD) is the most popular approach in extreme value statistics. This method typically requires high th...

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