Nonstationary Gaussian Process Models Using Spatial Hierarchical Clustering from Finite Differences
Author:
Affiliation:
1. Department of Statistics, Brigham Young University, Provo, UT 84602 ()
2. Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203()
Publisher
Informa UK Limited
Subject
Applied Mathematics,Modelling and Simulation,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/00401706.2015.1102763
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1. Identifying clusters in Bayesian disease mapping
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