plgp

cranv1.1-13

Particle Learning of Gaussian Processes. Sequential Monte Carlo (SMC) inference for fully Bayesian Gaussian process (GP) regression and classification models by particle learning (PL) following Gramacy & Polson (2011) <doi:10.48550/arXiv.0909.5262>. The sequential nature of inference and the active learning (AL) hooks provided facilitate t

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https://CRAN.R-project.org/package=plgp
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plyr (adjacent_swap_or_double dist 2)png (close_name dist 2)plm (close_name dist 2)

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First published · 2026-01-21 15:02:09

Last updated · 2026-01-21T14:00:02+00:00