# --------------------------------------------
# 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 "xnet" in publications use:'
type: software
license: GPL-3.0-only
title: 'xnet: Two-Step Kernel Ridge Regression for Network Predictions'
version: 0.1.11
identifiers:
- type: doi
  value: 10.32614/CRAN.package.xnet
abstract: Fit a two-step kernel ridge regression model for predicting edges in networks,
  and carry out cross-validation using shortcuts for swift and accurate performance
  assessment (Stock et al, 2018 <https://doi.org/10.1093/bib/bby095> ).
authors:
- family-names: Meys
  given-names: Joris
  email: Joris.Meys@UGent.be
- family-names: Stock
  given-names: Michiel
  email: Michiel.Stock@UGent.be
preferred-citation:
  type: manual
  title: 'xnet: Two-Step Kernel Ridge Regression for Network Predictions'
  authors:
  - family-names: Meys
    given-names: Joris
    email: Joris.Meys@UGent.be
  - family-names: Stock
    given-names: Michiel
    email: Michiel.Stock@UGent.be
  year: '2020'
  notes: R package version 0.1.11
  url: https://github.com/CenterForStatistics-UGent/xnet
repository: https://centerforstatistics-ugent.r-universe.dev
repository-code: https://github.com/CenterForStatistics-UGent/xnet
commit: 4093905ae81281b6cf81c6a3425bdaf884e78fb4
url: https://github.com/CenterForStatistics-UGent/xnet
date-released: '2020-02-03'
contact:
- family-names: Meys
  given-names: Joris
  email: Joris.Meys@UGent.be
references:
- type: article
  title: Algebraic shortcuts for leave-one-out crossvalidation in supervised network
    inference.
  authors:
  - family-names: Stock
    given-names: Michiel
  - family-names: Pahikkala
    given-names: Tapio
  - family-names: Airola
    given-names: Antti
  - family-names: Waegeman
    given-names: Willem
  - family-names: Baets
    given-names: Bernard
    name-particle: de
  journal: Briefings in Bioinformatic
  year: '2018'
  doi: 10.1093/bib/bby095
  start: bby095
- type: article
  title: A comparative study of pairwise learning methods based on Kernel Ridge Regression
  authors:
  - family-names: Stock
    given-names: Michiel
  - family-names: Pahikkala
    given-names: Tapio
  - family-names: Airola
    given-names: Antti
  - family-names: Baets
    given-names: Bernard
    name-particle: de
  - family-names: Waegeman
    given-names: Willem
  journal: Neural Computation
  year: '2018'
  volume: '30'
  issue: '8'
  doi: 10.1162/neco_a_01096
  start: 2245-2283