Package: ACV 1.0.2

ACV: Optimal Out-of-Sample Forecast Evaluation and Testing under Stationarity

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>.

Authors:Filip Stanek [aut, cre]

ACV_1.0.2.tar.gz
ACV_1.0.2.zip(r-4.5)ACV_1.0.2.zip(r-4.4)ACV_1.0.2.zip(r-4.3)
ACV_1.0.2.tgz(r-4.4-any)ACV_1.0.2.tgz(r-4.3-any)
ACV_1.0.2.tar.gz(r-4.5-noble)ACV_1.0.2.tar.gz(r-4.4-noble)
ACV_1.0.2.tgz(r-4.4-emscripten)ACV_1.0.2.tgz(r-4.3-emscripten)
ACV.pdf |ACV.html✨
ACV/json (API)

Peer review:

Bug tracker:https://github.com/stanek-fi/acv/issues

On CRAN:

7 exports 1 stars 0.75 score 45 dependencies 5 scripts 348 downloads

Last updated 2 years agofrom:de3f903845. Checks:OK: 7. Indexed: yes.

Exports:estimateLestimateLongRunVarestimateRhoinfoPhishiftMatrixtestLtsACV

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo