Completed projects

Penalized Complexity-priors

Penalized Complexity-priors: A new tool to define default priors and robustify Bayesian models is a Norwegian Research Council supported project, and its main objective is to develop a new framework for specifying a class of default priors at model level. This will not only facilitate the ways priors are determined in practice but also robustify Bayesian analyses. The results will be made available in the R-INLA package.

Knowledge Based Non-Stationary Modeling

The project is supported by the Norwegian Research Council and is based on collaboration between researchers in statistics, quantitative genetics and hydrology. From a statisticians point of view, the goal is to develop statistical methods and knowledge for non-stationary processes.

The aim of the project is to contribute toward solving two important challenges, get better understanding about non-stationarity, and what data that are needed to detect it.

• Quantitative genetics challenge: Predict breeding values and identifying quantitative trait loci from SNP-panel data and pedigree information.
• Hydrology challenge: The problem of ungauged basins, i.e. challenge of estimating streamflow variables for locations where no streamflow observations are available.

Uncertainty in Reservoir Evaluation

Uncertainty in Reservoir Evaluation (URE) is supported by the Norwegian Research Council and a number of petroleum companies. The vision is to provide creative, mathematically based solutions to recognized challenges in reservoir evaluation, and to develop methodologies for analysis of spatial and spatio-temporal phenomena.