Package: accuracylevel
Title: Robust Accuracy-Level Metrics for Predictive Model Evaluation
Version: 0.1.0
Authors@R: c(
    person("Achmad Syahrul", "Choir", email = "madsyair@stis.ac.id",
    role = c("cre", "aut")),
    person("Mety", "Agustini", email = "mety.assahid@bps.go.id",
    role = "aut"),
    person("Kartika", "Fithriasari", email = "kartika_f@statistika.its.ac.id",
    role = "aut"),
    person("Dedy Dwi", "Prastyo", email = "dedy-dp@statistika.its.ac.id",
    role = "aut"))
Author: Achmad Syahrul Choir [cre, aut],
  Mety Agustini [aut],
  Kartika Fithriasari [aut],
  Dedy Dwi Prastyo [aut]
Maintainer: Achmad Syahrul Choir <madsyair@stis.ac.id>
Description: Implements novel accuracy-level metrics for evaluating continuous
    data prediction models. Four metrics are provided: Counted Squared Error
    (CSE), Counted Absolute Error (CAE), Counted Absolute Percentage Error
    (CAPE), and Symmetric Counted Absolute Percentage Error (SCAPE). These
    metrics offer robust, consistent, and interpretable evaluation on a 0-100%
    scale, addressing limitations of conventional metrics like RMSE, MAE, and
    MAPE. The package integrates with 'caret', 'tidymodels', and common
    forecasting frameworks. Based on Agustini, Fithriasari, and Prastyo (2026)
    <doi:10.1016/j.dajour.2025.100661>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/madsyair/accuracylevel
BugReports: https://github.com/madsyair/accuracylevel/issues
Depends: R (>= 3.5.0)
Imports: stats, graphics, utils
Suggests: rlang (>= 0.4.0), caret, yardstick, forecast, testthat (>=
        3.0.0), knitr, rmarkdown, ggplot2, tibble, dplyr
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Config/roxygen2/version: 8.0.0
Packaged: 2026-06-10 15:53:03 UTC; madsyair
Repository: CRAN
Date/Publication: 2026-06-18 13:20:02 UTC
Built: R 4.5.2; ; 2026-06-18 14:47:56 UTC; unix
