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deepgp

1.2.3Package record

Bayesian Deep Gaussian Processes using MCMC

0packages depend
6.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Performs Bayesian posterior inference for deep Gaussian processes following Sauer, Gramacy, and Higdon (2023, doi:10.48550/arXiv.2012.08015). See Sauer (2023, http://hdl.handle.net/10919/114845) for comprehensive methodological details and https://bitbucket.org/gramacylab/deepgp-ex/ for a variety of coding examples. Models are trained through MCMC including elliptical slice sampling of latent Gaussian layers and Metropolis-Hastings sampling of kernel hyperparameters. Gradient-enhancement and gradient predictions are offered following Booth (2026, doi:10.48550/arXiv.2512.18066). Vecchia approximation for faster computation is implemented following Sauer, Cooper, and Gramacy (2023, doi:10.48550/arXiv.2204.02904). Optional monotonic warpings are implemented following Barnett et al. (2025, doi:10.48550/arXiv.2408.01540). Downstream tasks include sequential design through active learning Cohn/integrated mean squared error (ALC/IMSE; Sauer, Gramacy, and Higdon, 2023), optimization through expected improvement (EI; Gramacy, Sauer, and Wycoff, 2022, doi:10.48550/arXiv.2112.07457), and contour location through entropy (Booth, Renganathan, and Gramacy, 2025, doi:10.48550/arXiv.2308.04420). Models extend up to three layers deep; a one layer model is equivalent to typical Gaussian process regression. Incorporates OpenMP and SNOW parallelization and utilizes C/C++ under the hood.

Install

Health

CRAN checks
13OK
Slowest check: 12.4 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-07-31
  • ERROR11 OK, 2 ERROR2026-07-30
  • OK13 OK2026-05-12
  • WARNING12 OK, 1 WARNING2026-05-11
Show 3 earlier changesHide 3 earlier changes
  • OK14 OK2026-04-22
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.2.3
READMEYes · 1,521 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
16includes a package overview page
Examples that run
19%3 run in a plain check · 4 only when donttest examples are enabled (R CMD check --as-cran) · 9 hold no code
Exported functions with examples
100%
Documented parameters
99%
Return-value docs
77%
Help pages citing references
69%
Vignettes (1)

Downloads

6.8K
CRAN downloads in the past year
Rank #5,359 · ~19/day · ~565/mo
Daily download trend is not available in this view yet.
50130 days
1.5K90 days
6.8K1 year
Compare downloads with other packages →
Also on416 r2u11 autocran

Dependencies

Declared dependencies
13 external dependencies (excludes base and recommended)

Installing deepgp adds 16 packages (9 with compiled code, 30 MB of source tarballs). Heaviest: BH 14 MB, fields 3.9 MB, spam 3.1 MB.

Depends (1)
R >= 3.6
Imports (13)
grDevicesgraphicsstatsdoParallelforeachparallelGpGpfieldsMatrixRcppmvtnormFNNabind
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer · added in 1.1.1

Maintainer since 0.1.0 (2020)

Listed in earlier versions (2)
no longer listed · 0.1.0 to 1.1.0
Booth
no longer listed · 1.1.3 to 1.2.3
Releases (15)

Pick two releases to compare their code metrics.

Show 6 earlier eventsHide 6 earlier events
  • 0.3.0
    record
    2021-11-24 · diff ↗ ·
    removed 2 exports
    EI, calc_K
  • 0.2.1
    record
    2021-07-15 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • 0.2.0
    record
    2020-12-16 · diff ↗ ·
    removed 1 export
    IMSPE
    added 1 export
    IMSE
  • 0.1.0
    record
    2020-10-29
  • R
    R 4.0.0 released · 2020-04-24

Package metadata

First published
2020-10-29
Total releases
15 / 6 yrs
License
LGPL
Minimum R
≥ 3.6
Download size
1.2 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("deepgp")
Booth, A. S. (2026). deepgp: Bayesian Deep Gaussian Processes using MCMC (Version 1.2.3) [Computer software]. https://doi.org/10.32614/CRAN.package.deepgp

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for deepgp version 1.2.3 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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