statlingua: Explain Statistical Output with Large Language Models
Transform complex statistical output into straightforward, understandable, and context-aware natural language descriptions using Large Language Models (LLMs), making complex analyses more accessible to individuals with varying statistical expertise. It relies on the 'ellmer' package to interface with LLM providers including OpenAI <https://openai.com/>, Google AI Studio <https://aistudio.google.com/>, and Anthropic <https://www.anthropic.com/> (API keys are required and managed via 'ellmer').
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Suggests: |
car, ellmer (≥ 0.2.0), ISLR2, knitr, lme4, lmerTest, MASS, mgcv, nlme, R6, rmarkdown, survival, tibble, tinytest |
| Published: |
2025-06-02 |
| DOI: |
10.32614/CRAN.package.statlingua |
| Author: |
Brandon M. Greenwell
 [aut, cre] |
| Maintainer: |
Brandon M. Greenwell <greenwell.brandon at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/bgreenwell/statlingua,
https://bgreenwell.github.io/statlingua/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
statlingua results |
Documentation:
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