metrica: Prediction Performance Metrics

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/>.

Version: 2.1.0
Depends: R (≥ 3.6.0)
Imports: stats, ggplot2, dplyr, rlang, tidyr, utils, DBI, RSQLite, ggpp, minerva, energy
Suggests: purrr, knitr, rmarkdown, apsimx, testthat (≥ 3.0.0)
Published: 2024-06-30
DOI: 10.32614/CRAN.package.metrica
Author: Adrian A. Correndo ORCID iD [aut, cre, cph], Luiz H. Moro Rosso ORCID iD [aut], Rai Schwalbert ORCID iD [aut], Carlos Hernandez ORCID iD [aut], Leonardo M. Bastos ORCID iD [aut], Luciana Nieto ORCID iD [aut], Dean Holzworth [aut], Ignacio A. Ciampitti ORCID iD [aut]
Maintainer: Adrian A. Correndo <acorrend at uoguelph.ca>
BugReports: https://github.com/adriancorrendo/metrica/issues
License: MIT + file LICENSE
URL: https://adriancorrendo.github.io/metrica/
NeedsCompilation: no
Citation: metrica citation info
Materials: README NEWS
In views: Agriculture
CRAN checks: metrica results

Documentation:

Reference manual: metrica.pdf
Vignettes: Cheatsheet
JOSS_publication
Shinyapp
APSIM import files
Classification metrics
Regression metrics
Classification case
Regression case

Downloads:

Package source: metrica_2.1.0.tar.gz
Windows binaries: r-devel: metrica_2.1.0.zip, r-release: metrica_2.1.0.zip, r-oldrel: metrica_2.1.0.zip
macOS binaries: r-release (arm64): metrica_2.1.0.tgz, r-oldrel (arm64): metrica_2.1.0.tgz, r-release (x86_64): metrica_2.1.0.tgz, r-oldrel (x86_64): metrica_2.1.0.tgz
Old sources: metrica archive

Reverse dependencies:

Reverse suggests: apsimx

Linking:

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