On nearest‐neighbor Gaussian process models for massive spatial data-Reference-Cited by-同舟云学术

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On nearest‐neighbor Gaussian process models for massive spatial data

Published:2016-08-04 Issue:5 Volume:8 Page:162-171
ISSN:1939-5108
Container-title:WIREs Computational Statistics
language:en
Short-container-title:WIREs Comp Stat

Author:

Datta Abhirup¹,Banerjee Sudipto²,Finley Andrew O.³⁴,Gelfand Alan E.⁵

Affiliation:

1. Department of Biostatistics University of Minnesota Minneapolis MN USA

2. Department of Biostatistics University of California Los Angeles CA USA

3. Department of Forestry Michigan State University East Lansing MI USA

4. Department of Geography Michigan State University East Lansing MI USA

5. Department of Statistical Science Duke University Durham NC USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1383

Reference39 articles.

1. Wiley Series in Probability and Statistics;Cressie NAC,2011

2. Gaussian Processes for Machine Learning

3. Hierarchical Modeling and Analysis for Spatial Data

4. Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets

5. Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis

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