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CRAN: Package bayesTLS

bayesTLS: Joint Bayesian 4PL Models for Thermal Load Sensitivity

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).

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: brms, dplyr, ggplot2, MASS, methods, patchwork, posterior, stats, tibble, utils
Suggests: cmdstanr, glmmTMB, here, pkgload, readxl, testthat (≥ 3.0.0), tidybayes, tidyr
Published: 2026-07-21
DOI: 10.32614/CRAN.package.bayesTLS
Author: Daniel W. A. Noble [aut, cre], Pieter A. Arnold [aut], Shinichi Nakagawa [aut], Patrice Pottier [aut]
Maintainer: Daniel W. A. Noble <daniel.noble at anu.edu.au>
BugReports: https://github.com/daniel1noble/bayesTLS/issues
License: CC BY 4.0
URL: https://github.com/daniel1noble/bayesTLS
NeedsCompilation: no
Additional_repositories: https://stan-dev.r-universe.dev
Citation: bayesTLS citation info
Materials: README, NEWS
CRAN checks: bayesTLS results

Documentation:

Reference manual: bayesTLS.html , bayesTLS.pdf

Downloads:

Package source: bayesTLS_1.0.0.tar.gz
Windows binaries: r-devel: bayesTLS_1.0.0.zip, r-release: bayesTLS_1.0.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): bayesTLS_1.0.0.tgz, r-oldrel (arm64): bayesTLS_1.0.0.tgz, r-release (x86_64): bayesTLS_1.0.0.tgz, r-oldrel (x86_64): bayesTLS_1.0.0.tgz

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