by Chris Miller, B.S. Integrated Science and Technology (ISAT)
When simulating a complex system, often one of the first steps is to identify the data generating process (DGP) that produced a collection of random variables. Distribution fitting is the name given to this analytical process, which is used to identify how a given data set may have been generated. Existing components within the R Statistical Software such as fitdistRplus have significant distribution fitting capabilities, however, they can be overwhelming for practitioners and students. This project introduces EasyDTF (“Easy Data Transformations and Fitting”), a new package for the R Statistical Software that streamlines the distribution fitting process. EasyDTF provides a family of functions that include best-guess distribution fitting with confidence ratings, simple summaries of distribution attributes such as skewness and kurtosis, and basic data transformation capabilities. With EasyDTF, functionality becomes more accessible for the beginning user while preserving much of the functionality typically only available to power users.