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Publications by the group in this area, see publication list Seminars are given irregularly, see seminar homepage Statistics division |
A joint project between the statistics division at the Department of Mathematics at the University of Oslo, and the Norwegian Computing Centre, financed by The Research Council of Norway in the BeMatA program. The principal aim is to graduate one PhD. candidate and fund one post doc (two years) inside the research area of Bayesian Hierarchical Models. A brief description of the project is given below.
People involved
Brief project descriptionA trend in statistical analysis has been to consider more and more complex models. Such highly structured stochastic systems require numerical algorithms for making inference, which is a field of extensive research. Model evaluation in this context has however not been seriously addressed. One reason is the formidable computational challenges involved. This project aims at developing tools for model evaluation in complex models, with special emphasis on Bayesian hierarchical models. Evaluation of the appropriateness of a model must involve what the aims of the constructed models are. In some substance sciences, the models themselves are the main interest, and are selected and validated to obtain improved scientific understanding. In other situations the models are primarily tools for estimating quantities of interest, and it is the model's ability to e.g. predict that has to be evaluated. In this project we shall be concerned with both global and focussed measures, and although our goal is to invent general tools, we will concentrate on some selected applications in telemobile communications and fisheries research. In the comparison of models, computational efficiency is crucial. Development of faster Markov chain Monte Carlo (MCMC) algorithms will be addressed with special emphasis on adaptive MCMC. |