ADP
0.1.6Adoption Probability, Triers and Users Rate of a New Product
Overview
Calculate users prevalence of a product based on the prevalence of triers in the population. The measurement of triers is relatively easy. It is just a question of whether a person tried a product even once in his life or not. On the other hand, The measurement of people who also adopt it as part of their life is more complicated since adopting an innovative product is a subjective view of the individual. Mickey Kislev and Shira Kislev developed a formula to calculate the prevalence of a product's users to overcome this difficulty. The current package assists in calculating the users prevalence of a product based on the prevalence of triers in the population. See for: Kislev, M. M., and S. Kislev (2020) doi:10.5539/ijms.v12n4p63.
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Code & Tests
- Cyclomatic complexity
- 3.0 median / 3 max
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
4 0 exported
Complexity
3 avg / 3 max
Call network
4 nodes / 0 edges
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.1.6Latest
- 0.1.52021-07-30 · diff ↗
- 0.1.32021-07-28
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-07-28
- Total releases
- 3 / 5 yrs
- License
- GPL-3 OSI
- Download size
- 3.5 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet