R Observatory: Metrics for haldensify version 0.2.8

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

haldensify needs hal9001, which CRAN will archive unless its check problems are fixed by Oct 29.

haldensify

0.2.8Package record

Highly Adaptive Lasso Conditional Density Estimation

2packages dependsuggested by 1

5.6Kdownloads / year

83.6%test coverage

13/13flavors OK

Overview

About

Maintained by Nima HejaziCRAN page ↗GitHub ↗Website ↗Issues ↗

An algorithm for flexible conditional density estimation based on application of pooled hazard regression to an artificial repeated measures dataset constructed by discretizing the support of the outcome variable. To facilitate flexible estimation of the conditional density, the highly adaptive lasso, a non-parametric regression function shown to estimate cadlag (RCLL) functions at a suitably fast convergence rate, is used. The use of pooled hazards regression for conditional density estimation as implemented here was first described for by Díaz and van der Laan (2011) doi:10.2202/1557-4679.1356. Building on the conditional density estimation utilities, non-parametric inverse probability weighted (IPW) estimators of the causal effects of additive modified treatment policies are implemented, using conditional density estimation to estimate the generalized propensity score. Non-parametric IPW estimators based on this can be coupled with undersmoothing of the generalized propensity score estimator to attain the semi-parametric efficiency bound (per Hejazi, Díaz, and van der Laan doi:10.48550/arXiv.2205.05777).

Changes in 0.2.8

As of September 2025:

Fix a documentation error in format_long_hazards per a CRAN warning that package references should "use package anchors, i.e., use \link[PKG]{FOO}" (see <https://github.com/nhejazi/haldensify/issues/44>).
Export the predict method of haldensify objects rather than registering it solely as an S3 method for the generic, allowing other packages to easily reference and export (see <https://github.com/nhejazi/haldensify/issues/45>). See <https://github.com/r-lib/roxygen2/issues/1322> for a suggestion to export the method predict.xy manually via a Roxygen2 export tag.

From NEWS.md in the release

Install

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

install.packages("haldensify", 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("nhejazi/haldensify")

Development version from nhejazi/haldensify. 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-haldensify

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-haldensify

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-haldensify

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: 6.7 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-07-04
WARNING12 OK, 1 WARNING2026-07-03
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.2.8

READMEYes · 1,169 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.2.8Citation fileYes · cites a publicationWebsiteYes · pkgdown

Cites a JOSS paper

Help pages: 16 (5 internal)
Examples that run: 100%8 run in a plain check
Exported functions with examples: 100%
Documented parameters: 79%
Return-value docs: 75%
Help pages citing references: 0% with a bibliography file

Vignettes (1)

Highly Adaptive Lasso Conditional Density Estimation HTML

How these are measured

Downloads

5.6K

CRAN downloads in the past year

Rank #5,549 · ~15/day · ~465/mo

Releases R versions

Daily download trend is not available in this view yet.

73330 days

1.5K90 days

5.6K1 year

Compare downloads with other packages →

Also on102 r2u7 autocran

How downloads are counted

Repository

nhejazi/haldensify ↗Account: nhejazi

19Stars

6Forks

3Open issues

0Open PRs

4Releases

229Commits

3Commit identities

machine-learningdensity-estimationnonparametric-regressionhighly-adaptive-lassopropensity-scoreconditional-density-estimatescausal-inferenceinverse-probability-weights

229 commits · Last activity 2026-05-12

Responsiveness

How these are sampled

PRs merged (all time): 90%
Median days to close, 50 most recently updated closed issues: 94
Median days to close, 50 most recently updated closed PRs: 0

How these are measured

PracticesBeta

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

Checks run against github.com/nhejazi/haldensify on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

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

Governance and community (1)

Contributing guide

Docs source (3)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-05-12

pkgdown site last built 2025-09-06

Coverage (1)

Coverage reporting (Codecov)

Show all practicesHide 3 practices

Reproducibility and dev environment (1)

Makefile

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

18 external dependencies (excludes base and recommended)

Installing haldensify adds 47 packages (22 with compiled code, 43 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)

R >= 3.2.0

Imports (15)

statsutilsdplyr tibble ggplot2 data.table matrixStats future.apply assertthat hal9001 origami (>= 1.0.7)stringr rlang scales Rdpack

LinkingTo (0)

none

Suggests (5)

testthat knitr rmarkdown covr future

Enhances (0)

none

Dependencies facing archival

CRAN will archive these unless their check problems are fixed by the date shown. This package needs each one to install.

hal9001fix by Oct 29

Dependency license breakdown →

Reverse dependencies

2direct

1indirect

Imports 2

Suggested by 1

Depends, Imports or LinkingTo, most downloaded first

txshift survML

Suggests, most downloaded first

CICI

How these are counted

Code & Tests

People & History

People (4)

Nima Hejazi

David Benkeser

Author

Mark van der Laan

Author, Thesis advisor

Rachael Phillips

Contributor · added in 0.2.1

Releases (6)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
0.2.8Latest
record
2025-09-02 · current release · diff ↗ ·
added 1 export
predict.haldensify
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
0.2.3
record
2022-02-09 · diff ↗
unarchivedReturned to CRAN
2022-01-28
0.2.2
record
2022-01-28 · diff ↗
archivedRemoved from CRAN
2021-11-03
requires archived package 'hal9001',
0.2.1
record
2021-10-08 · diff ↗ ·
added 1 export
ipw_shift
R
R 4.1.0 released · 2021-05-18
0.0.6
record
2020-09-16 · diff ↗ ·
added 1 export
fit_haldensify
R
R 4.0.0 released · 2020-04-24
0.0.5
record
2020-03-14
R
R 3.6.0 released · 2019-04-26

Package metadata

First published: 2020-03-14
Total releases: 6 / 6 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 3.2.0
Download size: 179 KB

Appears in task views

Causal Inference

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("haldensify")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

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 haldensify version 0.2.8 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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