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
RoxygenNote: 7.1.2
Imports: forecast, Matrix, methods, stats
Depends:
Suggests: testthat
NeedsCompilation: no
Packaged: 2022-04-01 12:13:06 UTC; stane
Author: Filip Stanek [aut, cre]
Maintainer: Filip Stanek <stanek.fi@gmail.com>
Repository: CRAN
Date/Publication: 2022-04-05 09:40:13 UTC
Built: R 4.6.0; ; 2026-04-28 13:38:02 UTC; unix
