R Observatory: Metrics for stgam version 1.2.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

stgam

1.2.1Package record

Spatially and Temporally Varying Coefficient Models Using Generalized Additive Models

0packages depend

3Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Lex ComberCRAN page ↗GitHub ↗Issues ↗

A framework for undertaking space and time varying coefficient models (varying parameter models) using a Generalized Additive Model (GAM) with smooths approach. The framework suggests the need to investigate for the presence and nature of any space-time dependencies in the data. It proposes a workflow that creates and refines an initial space-time GAM and includes tools to create and evaluate multiple model forms. The workflow sequence is to: i) Prepare the data by lengthening it to have a single location and time variables for each observation. ii) Create all possible space and/or time models in which each predictor is specified in different ways in smooths. iii) Evaluate each model via their AIC value and pick the best one. iv) Create the final model. v) Calculate the varying coefficient estimates to quantify how the relationships between the target and predictor variables vary over space, time or space-time. vi) Create maps, time series plots etc. The number of knots used in each smooth can be specified directly or iteratively increased. This is illustrated with a climate point dataset of the dry rain forest in South America. This builds on work in Comber et al (2024) doi:10.1080/13658816.2023.2270285 and Comber et al (2026) doi:10.1080/13658816.2026.2671964.

Changes in 1.2.1

update to main function (evaluate_models()) with fast GAM option using mgcv::bam
update to gam_model_rank() function to include k in the results

From NEWS.md in the release

Install

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

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

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

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("lexcomber/stgam")

Development version from lexcomber/stgam. Installs pak first if it is not already available.

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-stgam

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-stgam

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-stgam

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: 9.1 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-08
NOTE12 OK, 1 NOTE2026-06-07
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.2.1

READMEYes · 319 wordsVignettesYes · 2 · dynamicNEWSYes · 67% structured · mentions 1.2.1Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 6 (1 internal)includes a package overview page
Examples that run: 80%4 run in a plain check · 1 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (2)

How these are measured

Downloads

3K

CRAN downloads in the past year

Rank #10,447 · ~8/day · ~252/mo

Releases R versions

Daily download trend is not available in this view yet.

34730 days

1K90 days

3K1 year

Compare downloads with other packages →

Also on118 r2u2 autocran

How downloads are counted

Repository

lexcomber/stgam ↗Account: lexcomber

7Stars

4Forks

1Open issues

2Open PRs

0Releases

164Commits

3Commit identities

164 commits · Last activity 2026-08-19

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: 1

Commits over time

2026-07-19 · 1602026-08-23 · 164

How these are measured

PracticesBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/lexcomber/stgam on 2026-10-25.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

18 external dependencies (excludes base and recommended)

Installing stgam adds 21 packages (11 with compiled code, 17 MB of source tarballs). Heaviest: stringi 11 MB, vctrs 1.0 MB, dplyr 902 KB.

Depends (3)

R >= 4.1.0mgcvglue

Imports (7)

foreach doParallelparalleldplyr magrittr purrr stringr

LinkingTo (0)

none

Suggests (11)

cols4all knitr ggplot2 cowplot rmarkdown testthat (>= 3.0.0)tidyr lubridate sf gratia kableExtra

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (4)

Lex Comber

Author, Maintainer since 0.0.1.0 (2024)

Chris Brunsdon

Contributor

Paul Harris

Contributor

Gonzalo Irisarri

Contributor · added in 1.2.0

Releases (9)

Pick two releases to compare their code metrics.

1.2.1Latest
record
2026-08-19 · current release · diff ↗
R
R 4.6.0 released · 2026-04-24
1.2.0
record
2026-01-29 · diff ↗ ·
added 1 export
effect_size
1.1.0
record
2025-08-27 · diff ↗
1.0.2
record
2025-06-12 · diff ↗
1.0.1
record
2025-06-07 · diff ↗
1.0.0
record
2025-05-12 · diff ↗ ·
removed 4 exports
do_bma, gam_model_probs, plot_1d_smooth, plot_2d_smooth

added 1 export
gam_model_rank
R
R 4.5.0 released · 2025-04-11
0.0.1.2
record
2024-07-31 · diff ↗
0.0.1.1
record
2024-07-12 · diff ↗
0.0.1.0
record
2024-06-25
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2024-06-25
Total releases: 9 / 2 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.1.0
Bundled data: 26 KB / 1 file
Download size: 3.3 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("stgam")

Format

Comber, L., Brunsdon, C., Harris, P., & Irisarri, G. (2026). stgam: Spatially and Temporally Varying Coefficient Models Using Generalized Additive Models (Version 1.2.1) [Computer software]. https://doi.org/10.32614/CRAN.package.stgam

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 stgam version 1.2.1 [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.

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