R Observatory: Metrics for wqspt version 1.0.2

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

wqspt

1.0.2Package record

Permutation Test for Weighted Quantile Sum Regression

0packages depend

2.2Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Drew DayCRAN page ↗

Implements a permutation test method for the weighted quantile sum (WQS) regression, building off the 'gWQS' package (Renzetti et al. https://CRAN.R-project.org/package=gWQS). Weighted quantile sum regression is a statistical technique to evaluate the effect of complex exposure mixtures on an outcome (Carrico et al. 2015 doi:10.1007/s13253-014-0180-3). The model features a statistical power and Type I error (i.e., false positive) rate trade-off, as there is a machine learning step to determine the weights that optimize the linear model fit. This package provides an alternative method based on a permutation test that should reliably allow for both high power and low false positive rate when utilizing WQS regression (Day et al. 2022 doi:10.1289/EHP10570).

Changes in 1.0.2

This function previously did not accommodate tibbles for the data argument

of wqs_full_perm, but now data can be a data.frame object or a tibble.

Added a utils.R script with a function get_legend2() to replace the

malfunctioning cowplot::get_legend() call in the function wqspt_plot. In

cowplot v1.1.3, get_legend() returns an error if the legend position is

anywhere besides on the right of the plot. Since wqspt_plot extracts a legend

positioned on the bottom of a plot to be included in the plot output if

InclKey = TRUE, this was previously throwing an error.

Added a gwqs_hpc function to utils.R along with its necessary hidden

functions imported from the gWQS package to add an option to specify a

number of workers for parallel processes for wqs_pt and wqs_full_perm. The

gwqs function in the gWQS package (v3.0.5) uses as many parallel processes

Show all changes in 1.0.2Hide the rest of the changes in 1.0.2

as there are cores detected, which can be problematic with high-performance

computing (HPC) environments. HPC schedulers allocate a specific number of

cores, and if gwqs tries to use more than that number, it will terminate the

HPC job. Therefore, gwqs_hpc was created to allow for the number of parallel

processes to be specified, thereby avoiding this problem.

Added ... arguments to wqs_pt and wqs_full_perm that ensure that the

additional arguments passed to gwqs_hpc are passed to every iteration of that

function, whereas previously those additional arguments only passed to the

main WQS regression in wqs_full_perm.

Added the arguments LegendWidthIn and LegendHeightIn to wqspt_plot to

control the bottom legend width and height, respectively.

Added some examples to the documentation for wqspt_plot to better illustrate

its use.

Replaced all b1_constr arguments with b_constr to match the change in the

name of this argument in the latest version of the gWQS package (v3.0.5).

Replaced URL links to referenced papers with doi.org links.
Added additional examples of papers using the WQSPT method.

From NEWS.md in the release

Install

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

install.packages("wqspt", 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-wqspt

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-wqspt

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-wqspt

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: 5.5 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.0.2

READMEYes · 277 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 1.0.2Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 4
Examples that run: 75%3 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 25%

Vignettes (1)

How to use the wqspt package HTML

How these are measured

Downloads

2.2K

CRAN downloads in the past year

Rank #19,599 · ~6/day · ~183/mo

Releases R versions

Daily download trend is not available in this view yet.

27830 days

67790 days

2.2K1 year

Compare downloads with other packages →

Also on64 r2u1 autocran

How downloads are counted

Dependencies

Declared dependencies

16 external dependencies (excludes base and recommended)

Installing wqspt adds 116 packages (61 with compiled code, 102 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)

R >= 3.5.0

Imports (16)

rlang gWQS pbapply ggplot2 mvtnorm viridis extraDistr cowplotmethodsMASScar future future.apply pscl reshape2nnet

LinkingTo (0)

none

Suggests (3)

rmarkdown knitr 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)

Drew Day

Author, Maintainer since 1.0.1 (2023)

James Peng

Author

Adam Szpiro

Author

Releases (2)

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
1.0.2Latest
record
2025-03-05 · current release · diff ↗
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
1.0.1
record
2023-03-06
R
R 4.2.0 released · 2022-04-22

Package metadata

First published: 2023-03-06
Total releases: 2 / 3 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.5.0
Download size: 4.2 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("wqspt")

Format

Day, D., Peng, J., & Szpiro, A. (2025). wqspt: Permutation Test for Weighted Quantile Sum Regression (Version 1.0.2) [Computer software]. https://doi.org/10.32614/CRAN.package.wqspt

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 wqspt version 1.0.2 [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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