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# CITATION 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 "oddnet" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'oddnet: Anomaly Detection in Temporal Networks'
version: 0.1.1.2
doi: 10.32614/CRAN.package.oddnet
abstract: Anomaly detection in dynamic, temporal networks. The package 'oddnet' uses
  a feature-based method to identify anomalies. First, it computes many features for
  each network. Then it models the features using time series methods. Using time
  series residuals it detects anomalies. This way, the temporal dependencies are accounted
  for when identifying anomalies (Kandanaarachchi, Hyndman 2022) <arXiv:2210.07407>.
authors:
- family-names: Kandanaarachchi
  given-names: Sevvandi
  email: sevvandik@gmail.com
  orcid: https://orcid.org/0000-0002-0337-0395
- family-names: Hyndman
  given-names: Rob
  email: rob.hyndman@monash.edu
  orcid: https://orcid.org/0000-0002-2140-5352
repository: https://robjhyndman.r-universe.dev
commit: c66aafdebb9139fd5b398d62acd11019ba18342c
url: https://sevvandi.github.io/oddnet/
contact:
- family-names: Kandanaarachchi
  given-names: Sevvandi
  email: sevvandik@gmail.com
  orcid: https://orcid.org/0000-0002-0337-0395