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:

Reference manual:	statlingua.pdf
Vignettes:	The statlingua Package (source)

Downloads:

Package source:	statlingua_0.1.0.tar.gz
Windows binaries:	r-devel: statlingua_0.1.0.zip, r-release: statlingua_0.1.0.zip, r-oldrel: statlingua_0.1.0.zip
macOS binaries:	r-release (arm64): statlingua_0.1.0.tgz, r-oldrel (arm64): statlingua_0.1.0.tgz, r-release (x86_64): statlingua_0.1.0.tgz, r-oldrel (x86_64): statlingua_0.1.0.tgz

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