gplite: Implementation for the Most Common Gaussian Process Models

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.

Package details

AuthorJuho Piironen [cre, aut]
MaintainerJuho Piironen <>
Package repositoryView on CRAN
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gplite documentation built on April 30, 2021, 5:09 p.m.