This is a collection of advice for modeling eDNA data with the artemis
package.
Center and scale your predictor values: artemis
uses MCMC to estimate values, and this will be more efficient if the predictor values are not on vastly different scales. In general, the MCMC will be the most efficient when the predictors are roughly centered at 0, and have sd of 1.
Use priors: The default priors in artemis
follow the conventions of the rstanarm
package, and are weakly informative. When the data do not strongly inform the parameter estimates, the model fit can be improved by specifying stronger priors.