Package: ForeComp
Type: Package
Title: Size-Power Tradeoff Visualization for Equal Predictive Ability
        of Two Forecasts
Version: 1.0.0
Author: Nathan Schor [aut],
  Minchul Shin [aut, cre, cph]
Maintainer: Minchul Shin <visiblehand@gmail.com>
Authors@R: c(
    person("Nathan", "Schor", role = "aut"),
    person("Minchul", "Shin",
           email = "visiblehand@gmail.com",
           role = c("aut", "cre", "cph"))
    )
Description: Offers tools for visualizing and analyzing size and power properties
    of tests for equal predictive accuracy, including Diebold-Mariano and
    related procedures. Provides multiple Diebold-Mariano test implementations
    based on fixed-smoothing approaches, including fixed-b methods such as
    Kiefer and Vogelsang (2005) <doi:10.1017/S0266466605050565>, and
    applications to tests for equal predictive accuracy as in Coroneo and
    Iacone (2020) <doi:10.1002/jae.2756>, alongside conventional large-sample
    approximations. HAR inference involves
    nonparametric estimation of the long-run variance, and a key tuning
    parameter (the truncation parameter) trades off size and power. Lazarus,
    Lewis, and Stock (2021) <doi:10.3982/ECTA15404> theoretically characterize
    the size-power frontier for the Gaussian multivariate location model.
    'ForeComp' computes and visualizes the finite-sample size-power frontier of
    the Diebold-Mariano test based on fixed-b asymptotics together with the
    Bartlett kernel. To compute finite-sample size and power, it fits a best
    approximating ARMA process to the input data and reports how the truncation
    parameter performs and how robust testing outcomes are to its choice.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/mcmcs/ForeComp
BugReports: https://github.com/mcmcs/ForeComp/issues
LazyData: true
Depends: R (>= 3.5.0), stats
Imports: forecast, astsa, ggplot2, rlang
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-02-20 15:14:00 UTC; mcs
Repository: CRAN
Date/Publication: 2026-02-20 15:40:07 UTC
Built: R 4.6.0; ; 2026-04-26 13:06:49 UTC; unix
