R Observatory: Metrics for haldensify version 0.2.8

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

haldensify

0.2.8

Highly Adaptive Lasso Conditional Density Estimation

3packages depend

6.9Kdownloads / year

83.6%test coverage

13/13checks pass

Overview

About

Maintained by Nima HejaziFirst published 2020-03-146 releasesCRAN page ↗GitHub ↗

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).

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.

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).

Health

CRAN checks

13OK

Slowest check: 7.0 min · r-devel-windows-x86_64

Code health

Yes

Tests · ratio 0.32

83.6%

Coverage · measured lines

100%

Documentation · exports

15

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-07-04
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
WARNING2026-07-03
12 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 1,169 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 79%
Return-value docs: 75%
References docs: 0%

Downloads

6.9K

CRAN downloads in the past year

Rank #8,739 · ~19/day · ~578/mo

Releases R versions

Daily download trend is not available in this view yet.

27130 days

1K90 days

6.9K1 year

Compare downloads with other packages →

Also on141 r2u26 autocran

Repository

GitHub ↗ nhejazi/haldensify

19Stars

6Forks

3Open issues

0Open PRs

4Releases

229Commits

3Contributors

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

229 commits · Last activity 2026-05-12

Repository practices

Upstream repositoryBeta

7 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/nhejazi/haldensify on 2026-08-23.

Continuous integration (1)

GitHub Actions

Reproducibility and dev environment (1)

Makefile

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Docs source (1)

README.Rmd

Show all practices

Lint, format, editor (1)

RStudio project

Coverage (1)

Codecov

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

18 external dependencies (excludes base and recommended)

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

Dependency license breakdown →

Reverse dependencies

3direct

1indirect

survML txshift CICI

Code & Tests

People & History

People (4)

Maintainer (1)

Nima Hejazi

Author, Maintainer, Copyright holder

Authors (3)

Nima Hejazi

Author, Maintainer, Copyright holder

David Benkeser

Author

Mark van der Laan

Author, Thesis advisor

Contributors (1)

Rachael Phillips

Contributor · added in 0.2.1

Copyright holders (1)

Nima Hejazi

Author, Maintainer, Copyright holder

Package Timeline

6 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
0.2.8Latest
2025-09-02 · current release · diff ↗
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
2022-02-09 · diff ↗
0.2.2
2022-01-28 · diff ↗
unarchivedReturned to CRAN
2022-01-28
archivedRemoved from CRAN
2021-11-03
requires archived package 'hal9001',
0.2.1
2021-10-08 · diff ↗
R
R 4.1.0 released · 2021-05-18
0.0.6
2020-09-16 · diff ↗
R
R 4.0.0 released · 2020-04-24
0.0.5
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
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Causal Inference

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("haldensify")

Format

Hejazi, N., Benkeser, D., Phillips, R., & van der Laan, M. (2025). haldensify: Highly Adaptive Lasso Conditional Density Estimation (Version 0.2.8) [Computer software]. https://doi.org/10.32614/CRAN.package.haldensify

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 v2026-08-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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