Bayesian concentration-response modelling using jagsNEC

This project used a suite of modern statistical methods to build robust tools for deriving probabilistic management thresholds from ecotoxicological data for use in water quality assessment and environmental risk assessment. This record documents the R packages developed under the project which proposed statistical solutions to account for uncertainty and appropriate methods for dealing with small samples:- bayesnec is a No-Effect-Concentration estimation package that uses brms to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating both ECX values, but more particularly NEC. - the jagsNEC is an R package to fit concentration(dose) - response curves to toxicity data, and derive No-Effect-Concentration (NEC), No-Significant-Effect-Concentration (NSEC), and Effect-Concentration (of specified percentage ‘x’, ECx) thresholds from non-linear models fitted using Bayesian MCMC fitting methods via the R2jags package and jags.

本项目采用一套现代统计方法，构建了稳健的工具集，用于从生态毒理学数据中推导概率管理阈值，以应用于水质评估与环境风险评估。本记录归档了本项目开发的R包，这些包提出了用以考量不确定性的统计解决方案，以及处理小样本数据的适配方法：
- bayesnec：一款无效应浓度估算R包，依托brms库采用贝叶斯方法拟合浓度（剂量）-响应数据，用于估算ECx值，尤其聚焦于无效应浓度（No-Effect-Concentration, NEC）的测算。
- jagsNEC：一款可将浓度（剂量）-响应曲线拟合至毒性数据的R包，可通过R2jags库与jags工具，借助贝叶斯马尔可夫链蒙特卡洛（Markov Chain Monte Carlo, MCMC）拟合方法，从非线性模型中推导无效应浓度（No-Effect-Concentration, NEC）、无显著效应浓度（No-Significant-Effect-Concentration, NSEC）以及指定百分比‘x’对应的效应浓度（Effect-Concentration of specified percentage ‘x’, ECx）阈值。