**Peruzzi M**, Banerjee S, Dunson DB, Finley AO (2021). Grid-Parametrize-Split (GriPS) for Improved Scalable Inference in Spatial Big Data Analysis. arxiv.org/abs/2101.03579

How can one improve the performance of posterior sampling algorithms for spatial regression models for large scale data? We target posterior sampling for Meshed Gaussian Processes and propose a strategy based on **gridding and parameter expansion**. We show that both computation time and MCMC efficiency in terms of effective sample size can be significantly improved using our methodologies.

**Data application**: LiDAR data over the Tanana forest in Alaska. Data size approximately 5 million.