Package: foretell 0.2.0
foretell: Projecting Customer Retention Based on Fader and Hardie Probability Models
Project Customer Retention based on Beta Geometric, Beta Discrete Weibull and Latent Class Discrete Weibull Models.This package is based on Fader and Hardie (2007) <doi:10.1002/dir.20074> and Fader and Hardie et al. (2018) <doi:10.1016/j.intmar.2018.01.002>.
Authors:
foretell_0.2.0.tar.gz
foretell_0.2.0.zip(r-4.5)foretell_0.2.0.zip(r-4.4)foretell_0.2.0.zip(r-4.3)
foretell_0.2.0.tgz(r-4.4-any)foretell_0.2.0.tgz(r-4.3-any)
foretell_0.2.0.tar.gz(r-4.5-noble)foretell_0.2.0.tar.gz(r-4.4-noble)
foretell_0.2.0.tgz(r-4.4-emscripten)foretell_0.2.0.tgz(r-4.3-emscripten)
foretell.pdf |foretell.html✨
foretell/json (API)
| # Install 'foretell' in R: |
| install.packages('foretell', repos = c('https://sriharitn.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sriharitn/foretell/issues
- customer_retention - Observed % Customers Surviving at Least 0-12 Years
- persistency_data - Drug persistency (retention) rates by different therapeutic class.
Last updated 6 years agofrom:bfc0ba0dab. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win | OK | Nov 05 2024 |
| R-4.5-linux | OK | Nov 05 2024 |
| R-4.4-win | OK | Nov 05 2024 |
| R-4.4-mac | OK | Nov 05 2024 |
| R-4.3-win | OK | Nov 05 2024 |
| R-4.3-mac | OK | Nov 05 2024 |
Dependencies:nloptr
