This event is a Webinar. Please register here.
Here is the Abstract:
The goal of the rstanarm package is to make it easier to use Bayesian estimation for most common regression models via Stan while preserving the traditional syntax that is used for specifying models in R and R packages like lme4 . In this webinar, Ben Goodrich , one of the developers of rstanarm, will introduce the most salient features of the package.
To demonstrate these features, we will fit a model to loan repayments data from Lending Club and show why, in order to make rational decisions for loan approval or interest rate determination, we need a full posterior distribution as opposed to point predictions available in non-Bayesian statistical software.
For an introduction to the rstanarm package, please refer to “How to Use the rstanarm Package” vignette.