Package: ACV
Title: Optimal Out-of-Sample Forecast Evaluation and Testing under
        Stationarity
Version: 1.0.2
Authors@R: 
    person(given = "Filip",
           family = "Stanek",
           role = c("aut", "cre"),
           email = "stanek.fi@gmail.com")
Description: Package 'ACV' (short for Affine Cross-Validation) offers
        an improved time-series cross-validation loss estimator which
        utilizes both in-sample and out-of-sample forecasting
        performance via a carefully constructed affine weighting
        scheme. Under the assumption of stationarity, the estimator is
        the best linear unbiased estimator of the out-of-sample loss.
        Besides that, the package also offers improved versions of
        Diebold-Mariano and Ibragimov-Muller tests of equal predictive
        ability which deliver more power relative to their conventional
        counterparts. For more information, see the accompanying
        article Stanek (2021) <doi:10.2139/ssrn.3996166>.
License: GPL (>=3)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
Imports: forecast, Matrix, methods, stats
Depends:
Suggests: testthat
Repository: https://stanek-fi.r-universe.dev
Date/Publication: 2022-04-01 12:16:09 UTC
RemoteUrl: https://github.com/stanek-fi/acv
RemoteRef: HEAD
RemoteSha: de3f903845bd97cebb7d54e3665cb866d0ac3bb3
NeedsCompilation: no
Packaged: 2026-10-18 09:33:19 UTC; root
Author: Filip Stanek [aut, cre]
Maintainer: Filip Stanek <stanek.fi@gmail.com>