CLVTools: Tools for Customer Lifetime Value Estimation

Probabilistic latent customer attrition models (also known as "buy-'til-you-die models") are used to predict future purchase behavior of customers. This package includes fast and accurate implementations of various probabilistic latent customer attrition models for non-contractual settings (e.g., retail business) with and without time-invariant and time-varying covariates. Currently, the package includes the Pareto/NBD model (Pareto/Negative-Binomial-Distribution), the BG/NBD mode (Beta-Gamma/Negative-Binomial-Distribution) and the GGom/NBD (Gamma-Gompertz/Negative-Binomial-Distribution) for the purchase and the attrition processes as well as the Gamma/Gamma model for the spending process. For reference to the Pareto/NBD model, see Schmittlein DC, Morrison DG, Colombo R (1987) <doi:10.1287/mnsc.33.1.1>, for the BG/NBD model, see Fader PS, Hardie BG, Lee K (2005) <doi:10.1287/mksc.1040.0098> and for the GGom/NBD model see Bemmaor AC, Glady N (2012) <doi:10.1287/mnsc.1110.1461>. For reference to the Gamma/Gamma model, see Fader PS, Hardie BG, Lee K (2005) <doi:10.1509/jmkr.2005.42.4.415>.

Version: 0.7.0
Depends: R (≥ 3.5.0), methods
Imports: data.table (≥ 1.12.0), foreach (≥ 1.5.0), ggplot2 (≥ 3.2.0), lubridate (≥ 1.7.8), Matrix (≥ 1.2-17), MASS, optimx (≥ 2019-12.02), stats, utils
LinkingTo: Rcpp (≥ 0.12.12), RcppArmadillo (≥ 0.9.500.2.0), RcppGSL (≥ 0.3.7)
Suggests: covr, doFuture, doParallel, future, knitr, rmarkdown, testthat
Published: 2020-08-26
Author: Patrick Bachmann [cre, aut], Jeffrey Naef [aut], Patrik Schilter [aut], Markus Meierer [aut], Niels Kuebler [aut]
Maintainer: Patrick Bachmann <patrick.bachmann at business.uzh.ch>
BugReports: https://github.com/bachmannpatrick/CLVTools/issues
License: GPL-3
URL: https://github.com/bachmannpatrick/CLVTools
NeedsCompilation: yes
SystemRequirements: C++11
Materials: NEWS
CRAN checks: CLVTools results

Downloads:

Reference manual: CLVTools.pdf
Vignettes: The CLVTools Package
Package source: CLVTools_0.7.0.tar.gz
Windows binaries: r-devel: CLVTools_0.7.0.zip, r-release: CLVTools_0.7.0.zip, r-oldrel: CLVTools_0.7.0.zip
macOS binaries: r-release: CLVTools_0.7.0.tgz, r-oldrel: CLVTools_0.7.0.tgz
Old sources: CLVTools archive

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