Smooth Regression - The Gamma Test and Tools
Overview
Finds causal connections in precision data, finds lags and embeddings in time series, guides training of neural networks and other smooth models, evaluates their performance, gives a mathematically grounded answer to the over-training problem. Smooth regression is based on the Gamma test, which measures smoothness in a multivariate relationship. Causal relations are smooth, noise is not. 'sr' includes the Gamma test and search techniques that use it. References: Evans & Jones (2002) doi:10.1098/rspa.2002.1010, AJ Jones (2004) doi:10.1007/s10287-003-0006-1.
- First release of full package with one vignette
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- WARNING12 OK, 1 WARNING2026-06-07
- OK14 OK2026-03-10
Documentation
- Help pages
- 12 (1 internal)includes a package overview page
- Examples that run
- 100%11 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Repository
4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/haythorn/sr on 2026-10-21.
Dependencies
Code & Tests
Datasets
People & History
- 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
- 0.1.0Latest2023-03-10 · current release
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-03-10
- Total releases
- 1 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 44 KB / 2 files
- Download size
- 291 KB
Cite
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Run in R for the authors' preferred citation:
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