A Multi-Resolution Approximation for Massive Spatial Datasets

Understanding the Ensemble Kalman Filter

(2016) Matthias Katzfuss et al.   AMERICAN STATISTICIAN

Parallel inference for massive distributed spatial data using low-rank models

(2016) Matthias Katzfuss et al.   STATISTICS AND COMPUTING

Analysis, Simulation and Prediction of Multivariate Random Fields with PackageRandomFields

(2015) Martin Schlather et al.   Journal of Statistical Software

Probabilistic Forecasting

(2014) Tilmann Gneiting et al.   Annual Review of Statistics and Its Application

Stochastic approximation of score functions for Gaussian processes

(2013) Michael L. Stein et al.   Annals of Applied Statistics

Bayesian nonstationary spatial modeling for very large datasets

(2013) Matthias Katzfuss   ENVIRONMETRICS

Estimation and Prediction in Spatial Models With Block Composite Likelihoods

(2013) Jo Eidsvik et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Limitations on low rank approximations for covariance matrices of spatial data

(2013) Michael L. Stein   Spatial Statistics

2010 Rietz lecture: When does the screening effect hold?

(2012) Michael L. Stein   ANNALS OF STATISTICS

Bayesian hierarchical spatio-temporal smoothing for very large datasets

(2012) Matthias Katzfuss et al.   ENVIRONMETRICS

Tapered Covariance: Bayesian Estimation and Asymptotics

(2012) Benjamin Shaby et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach

(2012) Moreno Bevilacqua et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

(2011) Huiyan Sang et al.   Annals of Applied Statistics

How Total Precipitable Water Vapor Anomalies Relate to Cloud Vertical Structure

(2011) John M. Forsythe et al.   JOURNAL OF HYDROMETEOROLOGY

A full scale approximation of covariance functions for large spatial data sets

(2011) Huiyan Sang et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach

(2011) Finn Lindgren et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Spatio-temporal smoothing and EM estimation for massive remote-sensing data sets

(2011) Matthias Katzfuss et al.   JOURNAL OF TIME SERIES ANALYSIS

Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions

(2011) N. Halko et al.   SIAM REVIEW

Fixed rank kriging for very large spatial data sets

(2010) Noel Cressie et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets

(2009) Cari G. Kaufman et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

A Spatio-Temporal Model for Mean, Anomaly, and Trend Fields of North Atlantic Sea Surface Temperature

(2009) Ricardo T. Lemos et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Bayesian Treed Gaussian Process Models With an Application to Computer Modeling

(2008) Robert B Gramacy et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Gaussian predictive process models for large spatial data sets

(2008) Sudipto Banerjee et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY