Data engineering and BI courses are free!
For abms objects, it returns the posterior mean, standard deviation, and 95% centered credible interval for each parameter. Additionally, it provides all explored models alongside the conditional Bayes factors and marginal Bayes factors estimator between the most probable model and the others that have arisen.
summary_gibbs(fit, BF = FALSE)A summary of the inference performed by the Bayesian model obtained by the gibbs_abms() function. The variables are:
A table with the posterior mean, standard deviation, and 95% centered credible interval for each parameter
A table with all explored models. If BF=TRUE, the conditional Bayes factors and marginal Bayes factors estimator between the most probable model and the others that have arisen are displayed.
An abms object. Such object is obtained by fitting a regression model with the gibbs_abms() function.
A logical object. if TRUE, then the Bayes factor comparison is shown.BF=FALSE by default.
## See \code{gibbs_abms()} help page function
Run the code above in your browser using DataLab