Skip to content

spBPS

2.0-1Package record

Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

1packages depend
38.1Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Provides functions for Bayesian Predictive Stacking within the Bayesian transfer learning framework for geospatial artificial systems, as introduced in "Bayesian Transfer Learning for Artificially Intelligent Geospatial Systems: A Predictive Stacking Approach" (Presicce and Banerjee, 2025) doi:10.48550/arXiv.2410.09504. This methodology enables efficient Bayesian geostatistical modeling, utilizing predictive stacking to improve inference across spatial datasets. The core functions leverage 'C++' for high-performance computation, making the framework well-suited for large-scale spatial data analysis in parallel and distributed computing environments. Designed for scalability, it allows seamless application in computationally demanding scenarios.

Install

Health

CRAN checks
13OK
Slowest check: 5.5 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • WARNING12 OK, 1 WARNING2026-06-08
  • OK13 OK2026-05-02
Show 4 earlier changesHide 4 earlier changes
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-03-26
  • ERROR4 OK, 2 NOTE, 8 ERROR2026-03-10
Advisories

none known

Documentation

In release 2.0-1
READMEYes · 262 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · does not mention 2.0-1Citation fileNoWebsiteYes · pkgdown
Help pages
28 (1 internal)includes a package overview page
Examples that run
0%5 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
75%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

38.1K
CRAN downloads in the past year
Rank #8,680 · ~105/day · ~3.2K/mo
Daily download trend is not available in this view yet.
41930 days
1.1K90 days
38.1K1 year
Compare downloads with other packages →
Also on387 r2u6 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
License file reads as GPL-3.0 · Last activity 2026-05-07
Responsiveness
not measured
PracticesBeta

7 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/lucapresicce/spbps on 2026-10-18.

Continuous integration (1)
GitHub Actions
Docs source (3)
pkgdown

GitHub Pages site last deployed 2026-05-07 · The repository has a site deploy workflow

pkgdown site last built 2026-05-07, before release 2.0-1 (2026-05-14)

CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
19 external dependencies (excludes base and recommended)

Installing spBPS adds 15 packages (15 with compiled code, 16 MB of source tarballs). Heaviest: clarabel 5.7 MB, Rcpp 1.8 MB, scs 1.8 MB.

Depends (1)
R >= 1.8.0
Imports (3)
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Depends, Imports or LinkingTo, most downloaded first

People & History

People (2)
Author, Maintainer since 0.0-4 (2024)
Releases (3)

Pick two releases to compare their code metrics.

  • 2.0-1Latest
    record
    2026-05-14 · current release · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • 1.0-1
    record
    2026-03-19 · diff ↗ ·
    removed 12 exports
    BPS_PseudoBMA, BPS_combine, BPS_post, BPS_post_MvT, BPS_pred, BPS_pred_MvT, BPS_weights, BPS_weights_MvT, arma_dist, conv_opt, expand_grid_cpp, forceSymmetry_cpp
    added 1 export
    spBPS
  • R
    R 4.5.0 released · 2025-04-11
  • 0.0-4
    record
    2024-10-25
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-10-25
Total releases
3 / 2 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 1.8.0
Download size
245 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("spBPS")
Presicce, L., & Banerjee, S. (2026). spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning (Version 2.0-1) [Computer software]. https://doi.org/10.32614/CRAN.package.spBPS

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 spBPS version 2.0-1 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, 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 →

Privacy choices

These apply to this browser and are stored on this device only. Nothing about your choice is sent to us.

Read the privacy policy