Large-scale spatial statistics

Finn Lindgren, University of Bath

Large spatial and spatio-temporal data sets lead to challenging statistical modelling and computational problems. In some cases one can use a low dimensional model, which allows a very large number of observations to be used. Unfortunately, a common situation is that the increased data size is coupled with a desire to perform analysis on finer scales. I will discuss a method for stochastic multiscale modelling, and how numerical methods for sparse linear systems might be used to construct direct prediction and conditional sampling methods, avoiding the more costly MCMC approaches.