Package: metrica
Title: Prediction Performance Metrics
Version: 2.1.0
Date: 2024-06-30
Authors@R: c(
    person("Adrian A.", "Correndo", email = "acorrend@uoguelph.ca", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-4172-289X")),
    person("Luiz H.", "Moro Rosso", email = "lhmrosso@ksu.edu", role = "aut", comment = c(ORCID = "0000-0002-8642-911X")),
    person("Rai", "Schwalbert", email = "rai.schwalbert@hotmail.com", role = "aut", comment = c(ORCID = "0000-0001-8488-7507")),
    person("Carlos", "Hernandez", email = "carlosh92@ksu.edu", role = "aut", comment = c(ORCID = "0000-0001-5171-2516")),
    person("Leonardo M.", "Bastos", email = "leonardombastos@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-8958-6527")),
    person("Luciana", "Nieto", email = "lnieto@ksu.edu", comment = c(ORCID = "0000-0002-7172-0799"), role = "aut"),
    person("Dean", "Holzworth", email = "dean.holzworth@csiro.au", role = "aut"),
    person("Ignacio A.", "Ciampitti", email = "ciampitti@ksu.edu", role = "aut", comment = c(ORCID = "0000-0001-9619-5129")))
Description: A compilation of more than 80 functions designed to
        quantitatively and visually evaluate prediction performance of
        regression (continuous variables) and classification
        (categorical variables) of point-forecast models (e.g. APSIM,
        DSSAT, DNDC, supervised Machine Learning). For regression, it
        includes functions to generate plots (scatter, tiles, density,
        & Bland-Altman plot), and to estimate error metrics (e.g. MBE,
        MAE, RMSE), error decomposition (e.g. lack of
        accuracy-precision), model efficiency (e.g. NSE, E1, KGE),
        indices of agreement (e.g. d, RAC), goodness of fit (e.g. r,
        R2), adjusted correlation coefficients (e.g. CCC, dcorr),
        symmetric regression coefficients (intercept, slope), and mean
        absolute scaled error (MASE) for time series predictions. For
        classification (binomial and multinomial), it offers functions
        to generate and plot confusion matrices, and to estimate
        performance metrics such as accuracy, precision, recall,
        specificity, F-score, Cohen's Kappa, G-mean, and many more. For
        more details visit the vignettes
        <https://adriancorrendo.github.io/metrica/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
Depends: R (>= 3.6.0)
Suggests: purrr, knitr, rmarkdown, apsimx, testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: stats, ggplot2, dplyr, rlang, tidyr, utils, DBI, RSQLite,
        ggpp, minerva, energy
VignetteBuilder: knitr
URL: https://adriancorrendo.github.io/metrica/
BugReports: https://github.com/adriancorrendo/metrica/issues
Config/pak/sysreqs: libgsl0-dev libicu-dev
Repository: https://adriancorrendo.r-universe.dev
Date/Publication: 2024-06-30 13:05:52 UTC
RemoteUrl: https://github.com/adriancorrendo/metrica
RemoteRef: HEAD
RemoteSha: f01f1cf5884af1b3607834d66761a316cdc83c0c
NeedsCompilation: no
Packaged: 2026-07-04 13:39:08 UTC; root
Author: Adrian A. Correndo [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-4172-289X>),
  Luiz H. Moro Rosso [aut] (ORCID:
    <https://orcid.org/0000-0002-8642-911X>),
  Rai Schwalbert [aut] (ORCID: <https://orcid.org/0000-0001-8488-7507>),
  Carlos Hernandez [aut] (ORCID: <https://orcid.org/0000-0001-5171-2516>),
  Leonardo M. Bastos [aut] (ORCID:
    <https://orcid.org/0000-0001-8958-6527>),
  Luciana Nieto [aut] (ORCID: <https://orcid.org/0000-0002-7172-0799>),
  Dean Holzworth [aut],
  Ignacio A. Ciampitti [aut] (ORCID:
    <https://orcid.org/0000-0001-9619-5129>)
Maintainer: Adrian A. Correndo <acorrend@uoguelph.ca>