gretl vs R
Side-by-side comparison for macOS
gretl
7.0Software package for econometric analysis
R
8.0Environment for statistical computing and graphics
| Metric | gretl | R |
|---|---|---|
| Category | Finance | Developer Tools |
| AI Score | 7.0 | 8.0 |
| 30-day Installs | 10 | 1.1K |
| 90-day Installs | 32 | 3.0K |
| 365-day Installs | 122 | 11.7K |
| Version | 2026b | 4.6.0,sonoma |
| Auto-updates | No | No |
| Deprecated | No | No |
| GitHub Stars | 12 | — |
| GitHub Forks | 6 | — |
| Open Issues | - | — |
| License | GPL-3.0 | — |
| Language | C | — |
| Last GitHub Commit | 1mo ago | — |
| First Seen | Dec 28, 2017 | Mar 2, 2019 |
Reviews
gretl
Gretl is an open-source econometric analysis tool offering a user-friendly interface for regression and time-series modeling, ideal for economists and data analysts seeking a powerful yet accessible solution.
Gretl provides tools for regression analysis, econometric modeling, and time-series forecasting.
Pros
- + Open-source with GPL-3.0 license allowing modifications and distribution
- + User-friendly interface accessible to both beginners and advanced users
- + Active maintenance with recent updates and contributions
Cons
- - No auto-update feature requiring manual checks for new versions
- - Smaller community leading to limited third-party resources and slower issue resolution
R
R is a powerful environment for statistical computing and graphics, widely used in academia and data science. It offers extensive packages and tools for data analysis, visualization, and machine learning, making it indispensable for researchers and statisticians.
R provides an environment for statistical analysis, data visualization, and programming.
Pros
- + Extensive statistical and graphical capabilities
- + Large ecosystem of packages and tools
- + Active and supportive community
Cons
- - Steep learning curve for beginners
- - Some enterprise features require additional tools