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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).

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 bayesTLS_1.0.0.tar.gz 468.7 KiB
1.0.0 rolling linux/noble R-4.5 bayesTLS_1.0.0.tar.gz 468.4 KiB
1.0.0 rolling source/ R- bayesTLS_1.0.0.tar.gz 246.6 KiB
1.0.0 latest linux/jammy R-4.5 bayesTLS_1.0.0.tar.gz 468.7 KiB
1.0.0 latest linux/noble R-4.5 bayesTLS_1.0.0.tar.gz 468.4 KiB
1.0.0 latest source/ R- bayesTLS_1.0.0.tar.gz 246.6 KiB
1.0.0 2026-04-23 source/ R- bayesTLS_1.0.0.tar.gz 0 B

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