BTYDplus: Probabilistic Models for Assessing and Predicting your Customer
Base
Provides advanced statistical methods to describe and predict customers'
purchase behavior in a non-contractual setting. It uses historic transaction records to fit a
probabilistic model, which then allows to compute quantities of managerial interest on a cohort-
as well as on a customer level (Customer Lifetime Value, Customer Equity, P(alive), etc.). This
package complements the BTYD package by providing several additional buy-till-you-die models, that
have been published in the marketing literature, but whose implementation are complex and non-trivial.
These models are: NBD [Ehrenberg (1959) <doi:10.2307/2985810>], MBG/NBD [Batislam et al (2007)
<doi:10.1016/j.ijresmar.2006.12.005>], (M)BG/CNBD-k [Reutterer et al (2020)
<doi:10.1016/j.ijresmar.2020.09.002>], Pareto/NBD (HB) [Abe (2009) <doi:10.1287/mksc.1090.0502>]
and Pareto/GGG [Platzer and Reutterer (2016) <doi:10.1287/mksc.2015.0963>].
Version: |
1.2.0 |
Depends: |
R (≥ 3.2.0) |
Imports: |
Rcpp, BTYD (≥ 2.3), coda, data.table, mvtnorm, bayesm, stats, graphics |
LinkingTo: |
Rcpp |
Suggests: |
testthat, covr, knitr, rmarkdown, gsl, lintr (≥ 1.0.0) |
Published: |
2021-01-21 |
DOI: |
10.32614/CRAN.package.BTYDplus |
Author: |
Michael Platzer [aut, cre] |
Maintainer: |
Michael Platzer <michael.platzer at gmail.com> |
BugReports: |
https://github.com/mplatzer/BTYDplus/issues |
License: |
GPL-3 |
URL: |
https://github.com/mplatzer/BTYDplus#readme |
NeedsCompilation: |
yes |
Materials: |
README NEWS |
CRAN checks: |
BTYDplus results |
Documentation:
Downloads:
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