Bayesian Inference of Binary, Count and Continuous Data in Toxicology
Checking object structure for analysis
Prepare data for Dose-Reponse
Extract simulation from the fit
Fits a Bayesian concentration-response model for target-time
Creates a data set for binary data analysis
Plotting method for BinaryData, CountData or ContinuousData.
Plot dose-response from DoseResponse objects
Plotting method for FitTT objects.
Plot the Posterior Predictive Chack on an object PPC
Plot an object XCX
Posterior Predictive Check data.frame for FitTT objects
Prediction base on FitTT
Return Prior and Posterior density of parameters of FitTT object
Predict X% Concentration at the target time (default).
Summary of FitTT object
Advanced methods for a valuable quantitative environmental risk assessment using Bayesian inference of several type of toxicological data. 'binary' (e.g., survival, mobility), 'count' (e.g., reproduction) and 'continuous' (e.g., growth as length, weight). Estimation procedures can be used without a deep knowledge of their underlying probabilistic model or inference methods. Rather, they were designed to behave as well as possible without requiring a user to provide values for some obscure parameters. That said, models can also be used as a first step to tailor new models for more specific situations.