Published December 3, 2024
| Version 1.1.6
Software
Open
bayesTPC: Bayesian inference for Thermal Performance Curves in R (version 1.1.6)
Creators
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1.
Virginia Tech
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2.
Columbia University
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3.
Montana State University System
Description
bayesTPC is an R package for fitting Thermal Performance Curves (TPCs) to trait response data. It uses the "nimble" language and machinery as the underlying engine for Markov Chain Monte Carlo (MCMC). bayesTPC aims to support the adoption of Bayesian approaches in thermal physiology, and promote TPC fitting that adequately quantifies uncertainty. This record is for version 1.1.6, corresponding to the version described in the paper submitted for publication titled "bayesTPC: Bayesian inference for Thermal Performance Curves in R". The file saved here is a tarball of the R package that can be directly installed in R by a user. For full code and dcoumentation/history see the GitHub repository:
https://github.com/johnwilliamsmithjr/bayesTPC
Files
Files
(1.0 MB)
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md5:e61ada1c41d70950b30aacda42fd1046
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Additional details
Related works
- Is described by
- Preprint: 10.1101/2024.04.25.591212 (DOI)
- Is variant form of
- Software: https://github.com/johnwilliamsmithjr/bayesTPC (URL)
Funding
- U.S. National Science Foundation
- Collaborative Research: CIBR: VectorByte: A Global Informatics Platform for studying the Ecology of Vector-Borne Diseases 2016264
- U.S. National Science Foundation
- CAREER: Quantifying heterogeneity and uncertainty in the transmission of vector borne dis- eases with a Bayesian trait-based framework 1750113
Software
- Repository URL
- https://github.com/johnwilliamsmithjr/bayesTPC
- Programming language
- R
- Development Status
- Active