Package: bayesTLS
Title: Joint Bayesian 4PL Models for Thermal Load Sensitivity
Version: 1.0.0
Authors@R: c(
    person("Daniel W. A.", "Noble",
           email = "daniel.noble@anu.edu.au",
           role  = c("aut", "cre")),
    person("Pieter A.", "Arnold", role = "aut"),
    person("Shinichi", "Nakagawa", role = "aut"),
    person("Patrice", "Pottier",
           email = "patrice.pottier@bioenv.gu.se",
           role  = "aut"))
Description: 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 (2026; bioRxiv). \doi{10.64898/2026.07.16.738378}.
License: CC BY 4.0
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
URL: https://github.com/daniel1noble/bayesTLS,
        https://www.biorxiv.org/content/10.64898/2026.07.16.738378v1
BugReports: https://github.com/daniel1noble/bayesTLS/issues
Imports: brms, dplyr, ggplot2, MASS, methods, patchwork, posterior,
        stats, tibble, utils
Suggests: cmdstanr, glmmTMB, here, pkgload, readxl, testthat (>=
        3.0.0), tidybayes, tidyr
Additional_repositories: https://stan-dev.r-universe.dev
Config/testthat/edition: 3
Depends: R (>= 4.1.0)
LazyData: true
Config/pak/sysreqs: make libicu-dev
Repository: https://daniel1noble.r-universe.dev
Date/Publication: 2026-07-23 02:47:14 UTC
RemoteUrl: https://github.com/daniel1noble/bayestls
RemoteRef: HEAD
RemoteSha: a9d5832356c60a503fc7bf75a3506702d1041cb8
NeedsCompilation: no
Packaged: 2026-07-23 05:07:29 UTC; root
Author: Daniel W. A. Noble [aut, cre],
  Pieter A. Arnold [aut],
  Shinichi Nakagawa [aut],
  Patrice Pottier [aut]
Maintainer: Daniel W. A. Noble <daniel.noble@anu.edu.au>