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FastGP

Efficiently Using Gaussian Processes with Rcpp and RcppEigen

Contains Rcpp and RcppEigen implementations of matrix operations useful for Gaussian process models, such as the inversion of a symmetric Toeplitz matrix, sampling from multivariate normal distributions, evaluation of the log-density of a multivariate normal vector, and Bayesian inference for latent variable Gaussian process models with elliptical slice sampling (Murray, Adams, and MacKay 2010).

Versions across snapshots

VersionRepositoryFileSize
1.2 rolling linux/jammy R-4.5 FastGP_1.2.tar.gz 402.8 KiB
1.2 rolling linux/noble R-4.5 FastGP_1.2.tar.gz 405.6 KiB
1.2 rolling source/ R- FastGP_1.2.tar.gz 317.0 KiB
1.2 latest linux/jammy R-4.5 FastGP_1.2.tar.gz 402.8 KiB
1.2 latest linux/noble R-4.5 FastGP_1.2.tar.gz 405.6 KiB
1.2 latest source/ R- FastGP_1.2.tar.gz 317.0 KiB
1.2 2026-04-26 source/ R- FastGP_1.2.tar.gz 317.0 KiB
1.2 2026-04-23 source/ R- FastGP_1.2.tar.gz 317.0 KiB
1.2 2026-04-09 windows/windows R-4.5 FastGP_1.2.zip 724.8 KiB
1.2 2025-04-20 source/ R- FastGP_1.2.tar.gz 317.0 KiB

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