R Observatory: Metrics for GPTreeO version 1.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

GPTreeO

1.1.0Package record

Dividing Local Gaussian Processes for Online Learning Regression

0packages depend

2.4Kdownloads / year

37.3%test coverage

13/13flavors OK

Overview

About

Maintained by Timo BraunCRAN page ↗

We implement and extend the Dividing Local Gaussian Process algorithm by Lederer et al. (2020) doi:10.48550/arXiv.2006.09446. Its main use case is in online learning where it is used to train a network of local GPs (referred to as tree) by cleverly partitioning the input space. In contrast to a single GP, 'GPTreeO' is able to deal with larger amounts of data. The package includes methods to create the tree and set its parameter, incorporating data points from a data stream as well as making joint predictions based on all relevant local GPs.

Changes in 1.1.0

Add option for continual forgetting by setting cont_forget_max_leaves
Add option to merge new point with existing point by setting merge_point_dist
Add verbose argument to control the amount of information the package prints to console
Perform additional training on the root node to have predictions available earlier
Allow for the user to set the number of residuals using use_n_residuals in the error_scaler
Add method to plot the tree structure plot_tree_structure
Add method to get the leaf_key for a training point get_leaf_key_from_training_point
Added vignette for basic GPTreeO functionality
Improve numerical stability of prediction uncertainty
Fixed bug that set user-specified gp_control$control to an empty list
Added option to not inherit GP optimization starting point from parent leaf by setting start_gp_opt_from_parent_pars
Add option to scale the lower and upper bound through bound_scale for the DiceKriging wrapper

Show all changes in 1.1.0Hide the rest of the changes in 1.1.0

For the DiceKriging wrapper, make local GP parameter choices more stable by reducing default bound_scale to 10 (was 100)
Minor code simplifications and efficiency improvements

From NEWS.md in the release

Install

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

install.packages("GPTreeO", 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-gptreeo

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-GPTreeO

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-GPTreeO

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: 2.9 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.1.0

READMENoVignettesYes · 2 · dynamicNEWSYes · 67% structured · mentions 1.1.0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 6
Examples that run: 100%1 run in a plain check
Exported functions with examples: 17%
Documented parameters: 100%
Return-value docs: 17%
Help pages citing references: 0%

Vignettes (2)

GPTreeO-Vignette PDF
Wrapper_creation_tutorial PDF

How these are measured

Downloads

2.4K

CRAN downloads in the past year

Rank #15,793 · ~7/day · ~201/mo

Releases R versions

Daily download trend is not available in this view yet.

26330 days

78890 days

2.4K1 year

Compare downloads with other packages →

Also on84 r2u3 autocran

How downloads are counted

Dependencies

Declared dependencies

13 external dependencies (excludes base and recommended)

Installing GPTreeO adds 50 packages (32 with compiled code, 48 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, igraph 4.8 MB.

Depends (0)

none

Imports (7)

R6 hash DiceKriging mlegp igraph ggraph ggplot2

LinkingTo (0)

none

Suggests (6)

knitr rmarkdown spelling testthat tidyr dplyr

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)

Timo Braun

Author, Maintainer since 1.0.0 (2024)

Anders Kvellestad

Author

Riccardo De Bin

Contributor

Releases (3)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
1.1.0Latest
record
2024-10-16 · current release · diff ↗
1.0.1
record
2024-10-16 · diff ↗
1.0.0
record
2024-09-23
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2024-09-23
Total releases: 3 / 2 yrs
License: MIT + file LICENSE OSI
Download size: 386 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GPTreeO")

Format

Braun, T., De Bin, R., & Kvellestad, A. (2026). GPTreeO: Dividing Local Gaussian Processes for Online Learning Regression (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.GPTreeO

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 GPTreeO version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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