rrunner/binsmlr: Creates Heterogenous Bins across a range of Ordinal values

The objective with the package is to perform a statistical optimal binning of ordinal values taking the default rate of each bin in consideration. The bins produced should be homogenous within and heterogenous across bins in terms of the default risk. A binning approach, as a data transformation, is generally feasible to credit risk portfolios having a relatively large number of defaults. A prerequisite is that each observation is assigned an ordinal value such as score or rating etc., that indicates the relative default risk as proposed by the rank ordering model. Also, a default indicator is required. Binning is common in different credit risk applications. See the binsmlr github page for more information.

install.packages("remotes")
remotes::install_github("rrunner/binsmlr")