bayesTLS
1.0.0Joint Bayesian 4PL Models for Thermal Load Sensitivity
Overview
Fits joint Bayesian four-parameter logistic (4PL) models to thermal-tolerance proportion data, extracts the classical thermal load sensitivity quantities (z, CTmax at 1 hour, T_crit) with full posterior uncertainty, and predicts heat-injury accumulation and survival under fluctuating temperature regimes with optional Sharpe-Schoolfield repair. Models are fitted with 'Stan' via the 'brms' package. Implements the framework described in Noble, Arnold, Nakagawa and Pottier (in preparation).
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- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-07-227 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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- Examples that run
- 43%
- Documented parameters
- 91%
- Return-value docs
- 100%
- References docs
- 0%
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Checks run against github.com/daniel1noble/bayestls on 2026-08-02.
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Uses AI-assisted development tooling (declared in repo)
Earliest detected marker: claude on 2026-04-21
Most recent: claude on 2026-04-21
- claude: on 2026-04-21 · evidence B, D
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1 release. R releases are shown for context.
- 1.0.0Latest2026-07-21 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-21
- Total releases
- 1 / 1 yrs
- License
- CC BY 4.0
- Additional repositories
- stan-dev.r-universe.dev
- Minimum R
- ≥ 4.1.0
- Bundled data
- 21 KB / 4 files
- Download size
- not tracked yet
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