TY - JOUR
T1 - bayesnec
T2 - An R Package for Concentration-Response Modeling and Estimation of Toxicity Metrics
AU - Fisher, Rebecca
AU - Barneche, Diego R.
AU - Ricardo, Gerard F.
AU - Fox, David R.
N1 - Publisher Copyright:
© 2024, American Statistical Association. All rights reserved.
PY - 2024/8/29
Y1 - 2024/8/29
N2 - The bayesnec package has been developed for R to fit concentration (dose)-response curves (CR) to toxicity data for the purpose of deriving no-effect-concentration (NEC), nosignificant- effect-concentration (NSEC), and effect-concentration (of specified percentage “x”, ECx) thresholds from non-linear models fitted using Bayesian Hamiltonian Monte Carlo (HMC) via R packages brms and rstan or cmdstanr. In bayesnec it is possible to fit a single model, custom model-set, specific model-set or all of the available models. When multiple models are specified, the bnec() function returns a model weighted average estimate of predicted posterior values. A range of support functions and methods is also included to work with the returned single, or multi-model objects that allow extraction of raw, or model averaged predicted, NEC, NSEC and ECx values and to interrogate the fitted model or model-set. By combining Bayesian methods with model averaging, bayesnec provides a single estimate of toxicity and associated uncertainty that can be directly integrated into risk assessment frameworks.
AB - The bayesnec package has been developed for R to fit concentration (dose)-response curves (CR) to toxicity data for the purpose of deriving no-effect-concentration (NEC), nosignificant- effect-concentration (NSEC), and effect-concentration (of specified percentage “x”, ECx) thresholds from non-linear models fitted using Bayesian Hamiltonian Monte Carlo (HMC) via R packages brms and rstan or cmdstanr. In bayesnec it is possible to fit a single model, custom model-set, specific model-set or all of the available models. When multiple models are specified, the bnec() function returns a model weighted average estimate of predicted posterior values. A range of support functions and methods is also included to work with the returned single, or multi-model objects that allow extraction of raw, or model averaged predicted, NEC, NSEC and ECx values and to interrogate the fitted model or model-set. By combining Bayesian methods with model averaging, bayesnec provides a single estimate of toxicity and associated uncertainty that can be directly integrated into risk assessment frameworks.
KW - Bayesian
KW - concentration-response
KW - no-effect-concentration
KW - non-linear modeling
UR - https://www.scopus.com/pages/publications/85211494138
U2 - 10.18637/jss.v110.i05
DO - 10.18637/jss.v110.i05
M3 - Article
AN - SCOPUS:85211494138
SN - 1548-7660
VL - 110
SP - 1
EP - 41
JO - Journal of Statistical Software
JF - Journal of Statistical Software
IS - 5
ER -