Package: bhetGP 1.0.2
bhetGP: Bayesian Heteroskedastic Gaussian Processes
Performs Bayesian posterior inference for heteroskedastic Gaussian processes. Models are trained through MCMC including elliptical slice sampling (ESS) of latent noise processes and Metropolis-Hastings sampling of kernel hyperparameters. Replicates are handled efficientyly through a Woodbury formulation of the joint likelihood for the mean and noise process (Binois, M., Gramacy, R., Ludkovski, M. (2018) <doi:10.1080/10618600.2018.1458625>) For large data, Vecchia-approximation for faster computation is leveraged (Sauer, A., Cooper, A., and Gramacy, R., (2023), <doi:10.1080/10618600.2022.2129662>). Incorporates 'OpenMP' and SNOW parallelization and utilizes 'C'/'C++' under the hood.
Authors:
bhetGP_1.0.2.tar.gz
bhetGP_1.0.2.zip(r-4.7)bhetGP_1.0.2.zip(r-4.6)bhetGP_1.0.2.zip(r-4.5)
bhetGP_1.0.2.tgz(r-4.6-x86_64)bhetGP_1.0.2.tgz(r-4.6-arm64)bhetGP_1.0.2.tgz(r-4.5-x86_64)bhetGP_1.0.2.tgz(r-4.5-arm64)
bhetGP_1.0.2.tar.gz(r-4.7-arm64)bhetGP_1.0.2.tar.gz(r-4.7-x86_64)bhetGP_1.0.2.tar.gz(r-4.6-arm64)bhetGP_1.0.2.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
bhetGP/json (API)
| # Install 'bhetGP' in R: |
| install.packages('bhetGP', repos = c('https://parulvpatil.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b16a326930. Checks:12 OK, 1 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 155 | ||
| linux-devel-x86_64 | OK | 166 | ||
| source / vignettes | OK | 198 | ||
| linux-release-arm64 | OK | 152 | ||
| linux-release-x86_64 | OK | 151 | ||
| macos-release-arm64 | OK | 266 | ||
| macos-release-x86_64 | OK | 300 | ||
| macos-oldrel-arm64 | OK | 146 | ||
| macos-oldrel-x86_64 | OK | 288 | ||
| windows-devel | OK | 163 | ||
| windows-release | OK | 169 | ||
| windows-oldrel | OK | 161 | ||
| wasm-release | FAIL | 124 |
Dependencies:BHclustercodetoolsDiceDesigndoParalleldotCall64fieldsFNNforeachGpGpGPvecchiahetGPiteratorslaGPlatticemapsmaptreeMASSMatrixmcomvtnormquadprogRColorBrewerRcppRcppArmadillorpartspamsparseinvtgpviridisLite
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Package bhetGP | bhetGP-package |
| MCMC sampling for Heteroskedastic GP | bhetGP |
| MCMC sampling for Heteroskedastic GP with variance changing in a subset of dimensions | bhetGP_vdims |
| MCMC sampling for Homoskedastic GP | bhomGP |
| Plots object from 'bhetGP' package | plot plot.bhetgp plot.bhetgp_vec plot.bhomgp plot.bhomgp_vec |
| Predict posterior mean and variance/covariance | predict predict.bhetgp predict.bhetgp_vec predict.bhomgp predict.bhomgp_vec |
| Trim/Thin MCMC iterations | trim |
