R Observatory: Metrics for ForecastingEnsembles version 0.5.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

ForecastingEnsembles

0.5.1Package record

Time Series Forecasting Using 23 Individual Models

0packages depend

3.1Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Russ ConteCRAN page ↗GitHub ↗Issues ↗

Runs multiple individual time series models, and combines them into an ensembles of time series models. This is mainly used to predict the results of the monthly labor market report from the United States Bureau of Labor Statistics for virtually any part of the economy reported by the Bureau of Labor Statistics, but it can be easily modified to work with other types of time series data. For example, the package was used to predict the winning men's and women's time for the 2024 London Marathon.

Install

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

install.packages("ForecastingEnsembles", 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("InfiniteCuriosity/ForecastingEnsembles")

Development version from InfiniteCuriosity/ForecastingEnsembles. 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-forecastingensembles

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-ForecastingEnsembles

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-ForecastingEnsembles

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: 2.7 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK12 OK2026-04-25

Show 1 earlier changeHide 1 earlier change

NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.5.1

READMEYes · 401 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 0.5.1Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 4
Examples that run: no examples
Exported functions with examples: 0%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

ForecastingEnsembles-vignette HTML

How these are measured

Downloads

3.1K

CRAN downloads in the past year

Rank #13,908 · ~8/day · ~257/mo

Releases R versions

Daily download trend is not available in this view yet.

30030 days

84390 days

3.1K1 year

Compare downloads with other packages →

Also on83 r2u3 autocran

How downloads are counted

Repository

infinitecuriosity/forecastingensembles ↗Account: InfiniteCuriosity

0Stars

0Forks

7Open issues

0Open PRs

0Releases

Last activity 2025-10-12

Responsiveness

not measured

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/infinitecuriosity/forecastingensembles on 2026-10-21.

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

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

Dependencies

Declared dependencies

20 external dependencies (excludes base and recommended)

Installing ForecastingEnsembles adds 125 packages (66 with compiled code, 98 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (22)

R >= 2.10distributional doParallel dplyr fable fabletools fable.prophet feasts fracdiff ggplot2 gt lubridate magrittrparallelreadr scalesstatstibble tidyr tsibble urcautils

Imports (0)

none

LinkingTo (0)

none

Suggests (2)

knitr rmarkdown

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 (1)

Russ Conte

Releases (2)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
0.5.1Latest
record
2025-10-13 · current release · diff ↗
R
R 4.5.0 released · 2025-04-11
0.5.0
record
2025-04-01
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2025-04-01
Total releases: 2 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 2.10
Bundled data: 4.2 KB / 3 files
Download size: 4.1 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ForecastingEnsembles")

Format

Conte, R. (2025). ForecastingEnsembles: Time Series Forecasting Using 23 Individual Models (Version 0.5.1) [Computer software]. https://doi.org/10.32614/CRAN.package.ForecastingEnsembles

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 ForecastingEnsembles version 0.5.1 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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