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gplite

General Purpose Gaussian Process Modelling

Implements the most common Gaussian process (GP) models using Laplace and expectation propagation (EP) approximations, maximum marginal likelihood (or posterior) inference for the hyperparameters, and sparse approximations for larger datasets.

Versions across snapshots

VersionRepositoryFileSize
0.13.0 rolling linux/jammy R-4.5 gplite_0.13.0.tar.gz 2.1 MiB
0.13.0 rolling linux/noble R-4.5 gplite_0.13.0.tar.gz 2.1 MiB
0.13.0 rolling source/ R- gplite_0.13.0.tar.gz 1.9 MiB
0.13.0 latest linux/jammy R-4.5 gplite_0.13.0.tar.gz 2.1 MiB
0.13.0 latest linux/noble R-4.5 gplite_0.13.0.tar.gz 2.1 MiB
0.13.0 latest source/ R- gplite_0.13.0.tar.gz 1.9 MiB
0.13.0 2026-04-26 source/ R- gplite_0.13.0.tar.gz 1.9 MiB
0.13.0 2026-04-23 source/ R- gplite_0.13.0.tar.gz 1.9 MiB
0.13.0 2026-04-09 windows/windows R-4.5 gplite_0.13.0.zip 2.4 MiB
0.13.0 2025-04-20 source/ R- gplite_0.13.0.tar.gz 1.9 MiB

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