Spatial modeling and inference with SPDE based Gaussian Markov Random Fields

Description

Gaussian random fields (GRFs) are a type of geostatistical model used in a range of spatial inference problems. In many such contexts data are available at a given spatial scale (or multiple scales), whereas inference or predictions are required at another scale that represents a different spatial configuration. We are in particular interested in downscaling in the context of global to local climate models, where GRFs play an important role, as a small number of parameters can be used to express a wide range of spatial properties. The GRF model of interest and the accompanying Bayesian inferential procedure use the INLA-SPDE approach. In this talk I will describe the GRF model, the inference procedure and simulation method and discuss challenges in this situation.

Period	07 Oct 2022
Event title	Workshop Junior female researchers in probability
Event type	Conference
Location	GermanyShow on map