# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "forecastdom" in publications use:' type: software license: MIT title: 'forecastdom: (Un)Conditional Forecast Dominance' version: 0.1.1 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) small-sample correction; the Clark-West mean squared forecast error (MSFE) adjusted statistic (Clark and West, 2007) ; the ENC-NEW encompassing test of Clark and McCracken (2001) ; the Giacomini-White conditional equal predictive ability test (Giacomini and White, 2006) ; Hansen's superior predictive ability (SPA) test (Hansen, 2005) ; the conditional superior predictive ability test of Li, Liao, and Quaedvlieg (2022) ; and the uniform and average multi-horizon SPA tests of Quaedvlieg (2021) . authors: - family-names: Cabrera given-names: Gabriel email: gabriel.cabrera.guz@gmail.com orcid: https://orcid.org/0000-0001-8803-2338 repository: https://cran.r-universe.dev repository-code: https://github.com/gabbocg/forecastdom commit: 4a93368af7df9bad3c712b456071dcf4f386a4b0 url: https://gabbocg.github.io/forecastdom/ date-released: '2026-11-01' contact: - family-names: Cabrera given-names: Gabriel email: gabriel.cabrera.guz@gmail.com orcid: https://orcid.org/0000-0001-8803-2338