R Observatory: Metrics for BayesNSGP version 0.3.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

BayesNSGP

0.3.1Package record

Bayesian Analysis of Non-Stationary Gaussian Process Models

0packages depend

3.6Kdownloads / year

5.2%test coverage

13/13flavors OK

Overview

About

Maintained by Daniel TurekCRAN page ↗

Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes can be specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary Gaussian processes are a special case of our methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial data sets (Finley, et al (2017) doi:10.48550/arXiv.1702.00434). Bayesian inference is carried out using Markov chain Monte Carlo methods via the "nimble" package, and posterior prediction for the Gaussian process at unobserved locations is provided as a post-processing step. Also provided are nearest-neighbor Gaussian process components for use directly in user-written model code, where the spatial process is retained as a latent field: neighbor-structure construction, a latent-field density and matching simulation function, a purpose-built Metropolis-Hastings sampler that updates the field one node at a time, and posterior prediction at unobserved locations.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("BayesNSGP", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-bayesnsgp

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-BayesNSGP

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-BayesNSGP

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 4.7 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-13
ERROR11 OK, 2 ERROR2026-09-12
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09

Show 2 earlier changesHide 2 earlier changes

ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3.1

READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 49
Examples that run: 95%19 run in a plain check · 1 never run
Exported functions with examples: 41%
Documented parameters: 100%
Return-value docs: 73%
Help pages citing references: 10%

How these are measured

Downloads

3.6K

CRAN downloads in the past year

Rank #6,845 · ~10/day · ~299/mo

Releases R versions

Daily download trend is not available in this view yet.

44430 days

1.3K90 days

3.6K1 year

Compare downloads with other packages →

Also on139 r2u36 autocran

How downloads are counted

Dependencies

Declared dependencies

6 external dependencies (excludes base and recommended)

Installing BayesNSGP adds 46 packages (27 with compiled code, 46 MB of source tarballs). Heaviest: sf 9.3 MB, ggplot2 6.0 MB, igraph 4.8 MB.

Depends (2)

R >= 3.4.0nimble

Imports (6)

FNNMatrixmethodsStatMatch sf ggplot2

LinkingTo (0)

none

Suggests (1)

testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (3)

Daniel Turek

Author, Maintainer since 0.1.0 (2019)

Fabian Ketwaroo

Author · added in 0.3.0

Mark Risser

Author

Releases (6)

Pick two releases to compare their code metrics.

0.3.1Latest
record
2026-09-10 · current release · diff ↗
0.3.0
record
2026-08-19 · diff ↗ ·
added 12 exports
NNGP.pred, RWNNGP_setup, computeAD, computeC, computeNeighbors, computeQF, displayNeighbors, dmnorm_NN_GP, expcov, get_single_reverse_neighbors, rmnorm_NN_GP, sampler_RW_NN_GP
R
R 4.6.0 released · 2026-04-24
0.2.0
record
2025-12-11 · diff ↗ ·
added 8 exports
Cy_sm, R_sparse_cholesky, R_sparse_solveMat, crossCy_sm, dmnorm_gp2Scale, nimble_sparse_cholesky, nimble_sparse_solveMat, rmnorm_gp2Scale
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.1.2
record
2022-01-09 · diff ↗
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
0.1.1
record
2019-10-12 · diff ↗
0.1.0
record
2019-08-29
R
R 3.6.0 released · 2019-04-26

Package metadata

First published: 2019-08-29
Total releases: 6 / 7 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.4.0
Download size: 70 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BayesNSGP")

Format

Turek, D., Ketwaroo, F., & Risser, M. (2026). BayesNSGP: Bayesian Analysis of Non-Stationary Gaussian Process Models (Version 0.3.1) [Computer software]. https://doi.org/10.32614/CRAN.package.BayesNSGP

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for BayesNSGP version 0.3.1 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →