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forecastdom
View on CRAN: Click
here
Download and install forecastdom package within the R console
Install from CRAN:
install.packages("forecastdom")
Install from Github:
library("remotes")
install_github("cran/forecastdom") Install by package version:
library("remotes")
install_version("forecastdom", "0.1.0") Attach the package and use:
library("forecastdom")
Maintained by
Gabriel Cabrera
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-24
Latest Update: 2026-07-24
Description:
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) <doi:10.1016/S0169-2070(96)00719-4> small-sample correction; the Clark-West MSFE-adjusted statistic (Clark and West, 2007) <doi:10.1016/j.jeconom.2006.05.023>; the ENC-NEW encompassing test of Clark and McCracken (2001) <doi:10.1016/S0304-4076(01)00071-9>; the Giacomini-White conditional equal predictive ability test (Giacomini and White, 2006) <doi:10.1111/j.1468-0262.2006.00718.x>; Hansen's superior predictive ability test (Hansen, 2005) <doi:10.1198/073500105000000063>; the conditional superior predictive ability test of Li, Liao, and Quaedvlieg (2022) <doi:10.1093/restud/rdab039>; and the uniform and average multi-horizon SPA tests of Quaedvlieg (2021) <doi:10.1080/07350015.2019.1620074>.
How to cite:
Gabriel Cabrera (2026). forecastdom: Tools for (Un)Conditional Forecast Dominance. R package version 0.1.0, https://cran.r-project.org/web/packages/forecastdom. Accessed 03 Oct. 2026.
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