Thanks for the hint with the error function, it’s really not clear in the help. I updated the help to

@param error function with signature f(mean, par) that generates observations with error (error = stochasticity according to what is assumed in the likelihood) from mean model predictions. Par is a vector from the matrix with the parameter samples (full length). f needs to know which of these parameters are parameters of the error function. See example in \code{\link{VSEM}}

]]>Thank you for your informations and package. I have been using this BayesianTools for estimating Posterior distribution of non-communicable disease model. I have a question “How can I turn these parameter chains into outcome chains”? Do you have an example code in your package if this is possible directly from the chains or if we have to rerun the model with parameters from the chains.

Best regards,

Wiriya