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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "forecastdom" in publications use:'
type: software
license: MIT
title: 'forecastdom: (Un)Conditional Forecast Dominance'
version: 0.1.0.9000
doi: 10.32614/CRAN.package.forecastdom
abstract: A unified toolkit for out-of-sample forecast dominance testing. Covers unconditional
  and conditional equal and superior predictive ability, encompassing, and nested-model
  comparison. Implements the Diebold-Mariano test with the Harvey, Leybourne, and
  Newbold (1997) <https://doi.org/10.1016/S0169-2070(96)00719-4> small-sample correction;
  the Clark-West mean squared forecast error (MSFE) adjusted statistic (Clark and
  West, 2007) <https://doi.org/10.1016/j.jeconom.2006.05.023>; the ENC-NEW encompassing
  test of Clark and McCracken (2001) <https://doi.org/10.1016/S0304-4076(01)00071-9>;
  the Giacomini-White conditional equal predictive ability test (Giacomini and White,
  2006) <https://doi.org/10.1111/j.1468-0262.2006.00718.x>; Hansen's superior predictive
  ability (SPA) test (Hansen, 2005) <https://doi.org/10.1198/073500105000000063>;
  the conditional superior predictive ability test of Li, Liao, and Quaedvlieg (2022)
  <https://doi.org/10.1093/restud/rdab039>; and the uniform and average multi-horizon
  SPA tests of Quaedvlieg (2021) <https://doi.org/10.1080/07350015.2019.1620074>.
authors:
- family-names: Cabrera
  given-names: Gabriel
  email: gabriel.cabrera.guz@gmail.com
  orcid: https://orcid.org/0000-0001-8803-2338
repository: https://gabbocg.r-universe.dev
repository-code: https://github.com/gabbocg/forecastdom
commit: 8965c741a6b0d8a1bb762491eb8811f2f49e250b
url: https://gabbocg.github.io/forecastdom/
date-released: '2026-08-20'
contact:
- family-names: Cabrera
  given-names: Gabriel
  email: gabriel.cabrera.guz@gmail.com
  orcid: https://orcid.org/0000-0001-8803-2338