Particle learning of Gaussian processes (plgp R package)


30/04/2010

plgp is an R package implementing sequential Monte Carlo inference for fully Bayesian Gaussian process (GP) models by particle learning (PL). The sequential nature of inference and the active learning (AL) hooks provided facilitate thrifty sequential design and optimization. This package essentially provides a generic PL interface, and functions (arguments to the interface) which implement the GP models and AL heuristics. The current version supports

This software is licensed under the GNU Lesser Public License (LGPL), version 2 or later. See the change log and an archive of previous versions.


Obtaining plgp

Documentation

References

Please send questions and comments to rbgramacy_AT (_chicagobooth_DOT_edu). Enjoy!


Robert B. Gramacy -- 2011

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