R Observatory: Metrics for CLVTools version 0.12.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

CLVTools

0.12.1Package record

Tools for Customer Lifetime Value Estimation

0packages depend

6.4Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Patrick BachmannCRAN page ↗GitHub ↗Issues ↗

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.

Changes in 0.12.1

NEW FEATURES

newcustomer() prediction: Include the initial transaction in the predicted number of orders

From NEWS.md in the release

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. 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-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). 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: 12.0 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK12 OK2026-04-25
ERROR11 OK, 2 NOTE, 1 ERROR2026-03-30
NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.12.1

README· In the repository, left out of the releaseVignettesYes · 4 · dynamicNEWSYes · 100% structured · mentions 0.12.1Citation fileNo

Help pages: 90 (38 internal)includes a package overview page
Examples that run: 4%1 run in a plain check · 22 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 75%
Help pages citing references: 26%

Vignettes (4)

How these are measured

Downloads

6.4K

CRAN downloads in the past year

Rank #4,506 · ~17/day · ~531/mo

Releases R versions

Daily download trend is not available in this view yet.

54230 days

1.9K90 days

6.4K1 year

Compare downloads with other packages →

Also on456 r2u14 autocran

How downloads are counted

Repository

bachmannpatrick/clvtools ↗Account: bachmannpatrick

59Stars

14Forks

29Open issues

2Open PRs

12Releases

207Commits

7Commit identities

r-packagercustomer-relationship-managementcustomer-lifetime-valueclv

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

Responsiveness

How these are sampled

PRs merged (all time): 96%
Median days to close, 50 most recently updated closed issues: 112
Median days to close, 50 most recently updated closed PRs: 2

Stars over time

2025-09-28 · 592026-07-07 · 59

How these are measured

PracticesBeta

8 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/bachmannpatrick/clvtools on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

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

Docs source (3)

pkgdown

GitHub Pages site last deployed 2025-11-06 · The repository has a site deploy workflow

Coverage (1)

Coverage reporting

CRAN release process (1)

cran-comments.md

Show all practicesHide 1 practice

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

19 external dependencies (excludes base and recommended)

Installing CLVTools adds 48 packages (23 with compiled code, 33 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, optimx 2.2 MB.

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.

How these are counted

Code & Tests

Datasets

People & History

People (6)

Patrick Bachmann

Maintainer since 0.5.0 (2020), 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

Releases (12)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
0.12.1Latest
record
2025-11-06 · current release · diff ↗
0.12.0
record
2025-09-22 · diff ↗
R
R 4.5.0 released · 2025-04-11
0.11.2
record
2024-12-02 · diff ↗ ·
added 1 export
newcustomer.spending
0.11.1
record
2024-10-13 · diff ↗
0.11.0
record
2024-08-17 · diff ↗ ·
added 4 exports
clv.bootstrapped.apply, newcustomer, newcustomer.dynamic, newcustomer.static
R
R 4.4.0 released · 2024-04-24
0.10.0
record
2023-10-23 · diff ↗ ·
added 2 exports
latentAttrition, spending
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.9.0
record
2022-01-09 · diff ↗ ·
added 1 export
as.clv.data
0.8.1
record
2021-10-19 · diff ↗
R
R 4.1.0 released · 2021-05-18
0.8.0
record
2021-03-23 · diff ↗
0.7.0
record
2020-08-26 · diff ↗

Show 3 earlier eventsHide 3 earlier events

0.6.0
record
2020-06-25 · diff ↗
0.5.0
record
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

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 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 CLVTools version 0.12.1 [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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