<reponame>UCIDataLab/uci-digital-evidence
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@article{galbraith2017analyzing,
  title={Analyzing user-event data using score-based likelihood ratios with marked point processes},
  author={<NAME> and <NAME>},
  journal={Digital Investigation},
  volume={22},
  pages={S106--S114},
  year={2017},
  publisher={Elsevier},
  html={https://doi.org/10.1016/j.diin.2017.06.009}
}

@article{galbraith2020quantifying,
  title={Quantifying the association between discrete event time series with applications to digital forensics},
  author={<NAME> and <NAME> and <NAME>},
  journal={Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  volume={183},
  number={3},
  pages={1005--1027},
  year={2020},
  publisher={Wiley Online Library},
  code={https://github.com/UCIDataLab/assocr},
  html={https://doi.org/10.1111/rssa.12549}
}

@article{galbraith2020statistical,
  title={Statistical methods for the forensic analysis of geolocated event data},
  author={<NAME> and <NAME> and <NAME>},
  journal={Forensic Science International: Digital Investigation},
  volume={33},
  pages={301009},
  year={2020},
  publisher={Elsevier},
  html={https://doi.org/10.1016/j.fsidi.2020.301009}
}

@book{galbraith2020statistical,
  title={Statistical Methods for the Forensic Analysis of User-Event Data},
  author={<NAME>},
  year={2020},
  publisher={University of California, Irvine},
  html={https://www.proquest.com/dissertations-theses/statistical-methods-forensic-analysis-user-event/docview/2428029461/se-2?accountid=14509}
}