# CSAFE TOOLS

CSAFE Tools is a software suite of state-of-the-art statistical libraries designed to assist practitioners in analyzing forensic data. This work was developed in collaboration with the Center for Statistics and Applications in Forensic Evidence (CSAFE) at Iowa State University and Omni Analytics Group.

The methods used in the handwriter package are open-source and transparent. The statistical methods employed in Scenario 1 are described in [1]. The underlying code is available as a GitHub repository. The statistical methods employed in Scenario 2 are described in [2, 3]. The underlying code is available as a GitHub repository. This repository contains the development version. The current version is available on the Comprehensive R Archive Network (CRAN).

## Bibliography

1. Johnson, Madeline Quinn, and Danica M. Ommen. 2022. "Handwriting identification using random forests and score‐based likelihood ratios." Statistical Analysis and Data Mining: The ASA Data Science Journal 15 (3): 357-375. https://doi.org/10.1002/sam.11566

2. Crawford, Amy M., Nicholas S. Berry, and Alicia L. Carriquiry. 2020. " A clustering method for graphical handwriting components and statistical writership analysis." Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (1): 41–60. https://doi.org/10.1002/sam.11488.

3. Crawford, Amy M., Danica M. Ommen, and Alicia L. Carriquiry. 2023. "A rotation-based feature and Bayesian hierarchical model for the forensic evaluation of handwriting evidence in a closed set." The Annals of Applied Statistics 17 (2). https://doi.org/10.1214/22-AOAS1662.