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4 papers · 2 filters
Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments
Pulong Ma, Emily L. Kang, Amy Braverman +1
Observing system simulation experiments (OSSEs) have been widely used as a rigorous and cost-effective way to guide development of new observing systems, and to evaluate the perfor…
Multi-Resolution Functional ANOVA for Large-Scale, Many-Input Computer Experiments
Chih-Li Sung, Wenjia Wang, Matthew Plumlee +1
The Gaussian process is a standard tool for building emulators for both deterministic and stochastic computer experiments. However, application of Gaussian process models is greatl…
Differentially private significance tests for regression coefficients
Andrés F. Barrientos, Jerome P. Reiter, Ashwin Machanavajjhala +1
Many data producers seek to provide users access to confidential data without unduly compromising data subjects' privacy and confidentiality. One general strategy is to require use…
A Fused Gaussian Process Model for Very Large Spatial Data
Pulong Ma, Emily L. Kang
With the development of new remote sensing technology, large or even massive spatial datasets covering the globe become available. Statistical analysis of such data is challenging.…