2 citations · 2 across the 1 of their papers we have counts for
5 papers
High Performance Multivariate Geospatial Statistics on Manycore Systems
Mary Lai O. Salvaña, Sameh Abdulah, Huang Huang +4
Modeling and inferring spatial relationships and predicting missing values of environmental data are some of the main tasks of geospatial statisticians. These routine tasks are acc…
Combining interdependent climate model outputs in CMIP5: A spatial Bayesian approach
Huang Huang, Dorit Hammerling, Bo Li +1
Projections of future climate change rely heavily on climate models, and combining climate models through a multi-model ensemble is both more accurate than a single climate model a…
Pushing the Limit: A Hybrid Parallel Implementation of the Multi-resolution Approximation for Massive Data
Huang Huang, Lewis R. Blake, Dorit M. Hammerling
The multi-resolution approximation (MRA) of Gaussian processes was recently proposed to conduct likelihood-based inference for massive spatial data sets. An advantage of the method…
Visualization and Assessment of Spatio-temporal Covariance Properties
Huang Huang, Ying Sun
Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random processes in geostatistical data. For second-order stationary processe…
Hierarchical low rank approximation of likelihoods for large spatial datasets
Huang Huang, Ying Sun
Datasets in the fields of climate and environment are often very large and irregularly spaced. To model such datasets, the widely used Gaussian process models in spatial statis- ti…