45 citations · 341 across the 31 of their papers we have counts for
37 papers
Joint species distribution models with imperfect detection for high-dimensional spatial data
Jeffrey W. Doser, Andrew O. Finley, Sudipto Banerjee
Determining spatial distributions of species and communities are key objectives of ecology and conservation. Joint species distribution models use multi-species detection-nondetect…
bayesassurance: An R package for calculating sample size and Bayesian assurance
Jane Pan, Sudipto Banerjee
We present a bayesassurance R package that computes the Bayesian assurance under various settings characterized by different assumptions and objectives. The package offers a constr…
Nonstationary Spatial Process Models with Spatially Varying Covariance Kernels
Sébastien Coube-Sisqueille, Sudipto Banerjee, Benoît Liquet
Building spatial process models that capture nonstationary behavior while delivering computationally efficient inference is challenging. Nonstationary spatially varying kernels (se…
Multi-group Gaussian Processes
Didong Li, Andrew Jones, Sudipto Banerjee +1
Gaussian processes (GPs) are pervasive in functional data analysis, machine learning, and spatial statistics for modeling complex dependencies. Modern scientific data sets are typi…
Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear Regression Framework
Sudipto Banerjee
Geographic Information Systems (GIS) and related technologies have generated substantial interest among statisticians with regard to scalable methodologies for analyzing large spat…
Inference for Gaussian Processes with Matérn Covariogram on Compact Riemannian Manifolds
Didong Li, Wenpin Tang, Sudipto Banerjee
Gaussian processes are widely employed as versatile modelling and predictive tools in spatial statistics, functional data analysis, computer modelling and diverse applications of m…