5 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
Statistical Downscaling of Model Projections with Multivariate Basis Graphical Lasso
Ayesha Ekanayaka, Emily Kang, Peter Kalmus +1
We describe an improved statistical downscaling method for Earth science applications using multivariate Basis Graphical Lasso (BGL). We demonstrate our method using a case study o…
Spatio-Temporal Data Fusion for Massive Sea Surface Temperature Data from MODIS and AMSR-E Instruments
Pulong Ma, Emily L. Kang
Remote sensing data have been widely used to study various geophysical processes. With the advances in remote-sensing technology, massive amount of remote sensing data are collecte…
An Additive Approximate Gaussian Process Model for Large Spatio-Temporal Data
Pulong Ma, Bledar A. Konomi, Emily L. Kang
Motivated by a large ground-level ozone dataset, we propose a new computationally efficient additive approximate Gaussian process. The proposed method incorporates a computational-…
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…
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.…