6 citations · 6 across the 1 of their papers we have counts for
3 papers
stat.ME2020★ 6 cited
Spatial Multivariate Trees for Big Data Bayesian Regression
Michele Peruzzi, David B. Dunson
High resolution geospatial data are challenging because standard geostatistical models based on Gaussian processes are known to not scale to large data sizes. While progress has be…
stat.ME2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
Michele Peruzzi, Sudipto Banerjee, Andrew O. Finley
We introduce a class of scalable Bayesian hierarchical models for the analysis of massive geostatistical datasets. The underlying idea combines ideas on high-dimensional geostatist…
stat.ME2018
Bayesian Modular and Multiscale Regression
Michele Peruzzi, David B. Dunson
We tackle the problem of multiscale regression for predictors that are spatially or temporally indexed, or with a pre-specified multiscale structure, with a Bayesian modular approa…