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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "processpredictR" in publications use:'
type: software
license: MIT
title: 'processpredictR: Process Prediction'
version: 0.1.1
doi: 10.32614/CRAN.package.processpredictR
abstract: 'Means to predict process flow, such as process outcome, next activity,
  next time, remaining time, and remaining trace. Off-the-shelf predictive models
  based on the concept of Transformers are provided, as well as multiple way to customize
  the models. This package is partly based on work described in Zaharah A. Bukhsh,
  Aaqib Saeed, & Remco M. Dijkman. (2021). "ProcessTransformer: Predictive Business
  Process Monitoring with Transformer Network" <https://doi.org/10.48550/arXiv.2104.00721>.'
authors:
- family-names: Esin
  given-names: Ivan
  email: ivan.esin@student.uhasselt
- family-names: Janssenswillen
  given-names: Gert
  email: gert.janssenswillen@uhasselt.be
repository: https://cranhaven.r-universe.dev
commit: 9fdd2f15bd94d5691cf89efdb2755634c043c88f
date-released: '2026-11-11'
contact:
- family-names: Janssenswillen
  given-names: Gert
  email: gert.janssenswillen@uhasselt.be