Work

Modeling massive spatial datasets using a conjugate Bayesian linear modeling framework

Year: 2020

Type: article

Source: Spatial Statistics

DOI: 10.1016/j.spasta.2020.100417

Author: Sudipto Banerjee

Institution: University of California, Los Angeles

Language: English

Topic: Spatial and Panel Data Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute of Environmental Health Sciences, Division of Mathematical Sciences, Division of Information and Intelligent Systems

Awards: III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions, Collaborative Research: High-Dimensional Spatial-Temporal Modeling and Inference for Large Multi-Source Environmental Monitoring Systems, G5733225247, G5839942973, G6178810629, G6200516691, G674838986, G8275022487

OpenAlex ID: W3004792015

FWCI: 2.493

Cites: 69

Cited by: 19

Related to: 10