Joint Bayesian 4PL Models for Thermal Load Sensitivity R package bayesTLS version 1.0.0 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). Software 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 Daniel W. A. Noble <daniel.noble@anu.edu.au> Comprehensive R Archive Network (CRAN) Daniel W. A. Noble [aut, cre], Pieter A. Arnold [aut], Shinichi Nakagawa [aut], Patrice Pottier [aut] CC BY 4.0 2026-07-21 application/tgz https://CRAN.R-project.org/package=bayesTLS doi:10.32614/CRAN.package.bayesTLS