bayesTLS 1.0.0

First release.

bayesTLS fits joint Bayesian four-parameter logistic (4PL) models to thermal-tolerance data and derives the classical thermal death time / thermal load sensitivity quantities from the posterior, so that every downstream quantity carries full uncertainty and is mutually consistent within a draw.

Model fitting

• standardize_data() maps a raw thermal-tolerance dataset (binomial counts or continuous proportions) onto the columns the model expects, and records the duration unit and centring used.
• fit_4pl() fits the joint 4PL with brms, in either the midpoint parameterisation or the direct CTmax/z parameterisation (ctmax = ~ ..., z = ~ ...), with moderators allowed on any sub-parameter.
• make_4pl_formula() and make_4pl_priors() expose the underlying brms formula and default priors for inspection or customisation.

Deriving thermal load sensitivity

• tls() derives z, CTmax and T_crit per moderator group from any fitted 4PL — including hand-written brms models — by evaluating the sub-parameters on a moderator x temperature grid with brms::posterior_linpred().
• tls_z(), tls_ctmax() and tls_tcrit() return the individual quantities; derive_tdt_curve() and derive_tdt_landscape() give the TDT curve and landscape.

Prediction under fluctuating temperatures

• predict_heat_injury() accumulates heat injury over an arbitrary temperature trace, with optional Sharpe-Schoolfield repair (repair_rate_schoolfield()).
• predict_survival_curves() propagates that injury to survival.
• make_temperature_scenarios() builds fluctuating-temperature scenarios.

Two-stage comparison

• ts_stage1(), ts_stage2(), ts_curve() and ts_ci() implement the conventional two-stage TDT workflow, for direct comparison against the joint model.

Plotting and diagnostics

• plot_tdt_curve(), plot_tdt_landscape(), plot_heat_injury(), plot_survival_curves(), plot_temperature_scenarios() and friends, all on a shared theme_tdt().
• diagnose_tdt_fit() and bayes_R2_tls() for fit checking.

Data

Four publicly available example datasets spanning lethal and sub-lethal endpoints: aphid_tdt, dsuzukii, snowgum_psii and zebrafish_o2.