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stat.CO2019
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…
stat.CO2018
Marginally Parametrized Spatio-Temporal Models and Stepwise Maximum Likelihood Estimation
Matthew Edwards, Stefano Castruccio, Dorit Hammerling
In order to learn the complex features of large spatio-temporal data, models with large parameter sets are often required. However, estimating a large number of parameters is often…