45 citations · 341 across the 31 of their papers we have counts for
5 papers · 1 filter
Spatial Modeling for Correlated Cancers Using Bivariate Directed Graphs
Leiwen Gao, Sudipto Banerjee, Abhirup Datta
Disease maps are an important tool in cancer epidemiology used for the analysis of geographical variations in disease rates and the investigation of environmental risk factors unde…
On identifiability and consistency of the nugget in Gaussian spatial process models
Wenpin Tang, Lu Zhang, Sudipto Banerjee
Spatial process models popular in geostatistics often represent the observed data as the sum of a smooth underlying process and white noise. The variation in the white noise is att…
Conjugate Nearest Neighbor Gaussian Process Models for Efficient Statistical Interpolation of Large Spatial Data
Shinichiro Shirota, Andrew O. Finley, Bruce D. Cook +1
A key challenge in spatial statistics is the analysis for massive spatially-referenced data sets. Such analyses often proceed from Gaussian process specifications that can produce…
Bayesian Inference for Finite Populations Under Spatial Process Settings
Alec M. Chan-Golston, Sudipto Banerjee, Mark S. Handcock
We develop a Bayesian model-based approach to finite population estimation accounting for spatial dependence. Our innovation here is a framework that achieves inference for finite…
Bayesian spatially varying coefficient models in the spBayes R package
Andrew O. Finley, Sudipto Banerjee
This paper describes and illustrates new functionality for fitting spatially varying coefficients models in the spBayes (version 0.4-2) R package. The new spSVC function uses a com…