The block-NNGP is a new Gaussian process approximation that groups locations into blocks, producing a sparse precision matrix for faster Bayesian inference on large spatial data.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Fast Bayesian inference of Block Nearest Neighbor Gaussian process for large data
The block-NNGP is a new Gaussian process approximation that groups locations into blocks, producing a sparse precision matrix for faster Bayesian inference on large spatial data.