R Observatory: Metrics for CLVTools version 0.12.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

CLVTools

0.12.1

Tools for Customer Lifetime Value Estimation

0packages depend

6Kdownloads / year

–test coverage

13/13checks pass

Overview

About

Maintained by Patrick BachmannFirst published 2020-05-0812 releasesCRAN page ↗GitHub ↗

A set of state-of-the-art probabilistic modeling approaches to derive estimates of individual customer lifetime values (CLV). Commonly, probabilistic approaches focus on modelling 3 processes, i.e. individuals' attrition, transaction, and spending process. Latent customer attrition models, which are also known as "buy-'til-you-die models", model the attrition as well as the transaction process. They are used to make inferences and predictions about transactional patterns of individual customers such as their future purchase behavior. Moreover, these models have also been used to predict individuals’ long-term engagement in activities such as playing an online game or posting to a social media platform. The spending process is usually modelled by a separate probabilistic model. Combining these results yields in lifetime values estimates for individual customers. This package includes fast and accurate implementations of various probabilistic models for non-contractual settings (e.g., grocery purchases or hotel visits). All implementations support time-invariant covariates, which can be used to control for e.g., socio-demographics. If such an extension has been proposed in literature, we further provide the possibility to control for time-varying covariates to control for e.g., seasonal patterns. Currently, the package includes the following latent attrition models to model individuals' attrition and transaction process: [1] Pareto/NBD model (Pareto/Negative-Binomial-Distribution), [2] the Extended Pareto/NBD model (Pareto/Negative-Binomial-Distribution with time-varying covariates), [3] the BG/NBD model (Beta-Gamma/Negative-Binomial-Distribution) and the [4] GGom/NBD (Gamma-Gompertz/Negative-Binomial-Distribution). Further, we provide an implementation of the Gamma/Gamma model to model the spending process of individuals.

Install

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

install.packages("CLVTools", 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("bachmannpatrick/CLVTools")

Development version from bachmannpatrick/CLVTools. 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-clvtools

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-CLVTools

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-CLVTools

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 12.2 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.85

not tracked

Coverage

100%

Documentation · exports

13

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
OK2026-04-25
12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-03-30
11 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 17%
Documented parameters: 100%
Return-value docs: 75%
References docs: 26%

Downloads

6K

CRAN downloads in the past year

Rank #7,411 · ~16/day · ~498/mo

Releases R versions

Daily download trend is not available in this view yet.

29130 days

1.2K90 days

6K1 year

Compare downloads with other packages →

Also on471 r2u19 autocran

Repository

GitHub ↗ bachmannpatrick/clvtools

59Stars

14Forks

29Open issues

2Open PRs

12Releases

207Commits

7Contributors

r-packagercustomer-relationship-managementcustomer-lifetime-valueclv

207 commits · Last activity 2025-11-06 · 0% stars, 30d

Stars over time

2025-05-20 · 572026-07-07 · 59

Repository practices

Upstream repositoryBeta

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

Checks run against github.com/bachmannpatrick/clvtools on 2026-08-09.

Continuous integration (1)

GitHub Actions

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

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

Dependencies

Declared dependencies

19 external dependencies (excludes base and recommended)

Depends (2)

R >= 3.5.0methods

Imports (12)

data.table digest Formula ggplot2 lubridate numDeriv (>= 2016.8-1.1)MatrixMASSoptimx Rcppstatsutils

LinkingTo (4)

Rcpp RcppArmadillo RcppGSL testthat

Suggests (7)

covr knitr rmarkdown xml2 testthat lmtest R.rsp

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (6)

Maintainer (1)

Patrick Bachmann

Maintainer, Author

Authors (6)

Maintainer, Author

Author

Author

Author

Author · added in 0.10.0

Patrik Schilter

Author

Listed in earlier versions (1)

Elliot Oblander

no longer listed · 0.8.0 to 0.9.0

Package Timeline

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

R
R 4.6.0 released · 2026-04-24
0.12.1Latest
2025-11-06 · current release · diff ↗
0.12.0
2025-09-22 · diff ↗
R
R 4.5.0 released · 2025-04-11
0.11.2
2024-12-02 · diff ↗
0.11.1
2024-10-13 · diff ↗
0.11.0
2024-08-17 · diff ↗
R
R 4.4.0 released · 2024-04-24
0.10.0
2023-10-23 · diff ↗
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.9.0
2022-01-09 · diff ↗
0.8.1
2021-10-19 · diff ↗
R
R 4.1.0 released · 2021-05-18
0.8.0
2021-03-23 · diff ↗
0.7.0
2020-08-26 · diff ↗

Show 3 earlier events

0.6.0
2020-06-25 · diff ↗
0.5.0
2020-05-08
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2020-05-08
Total releases: 12 / 6 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.5.0
Bundled data: 104 KB / 5 files
Download size: 2.1 MB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("CLVTools")

Format

Bachmann, P., Kuebler, N., Meierer, M., Naef, J., Oblander, E. S., & Schilter, P. (2025). CLVTools: Tools for Customer Lifetime Value Estimation (Version 0.12.1) [Computer software]. https://doi.org/10.32614/CRAN.package.CLVTools

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 CLVTools version 0.12.1 [Data set]. HJJB, LLC. Data release v2026-08-11. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-11, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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