The R Journal: accepted article

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Measurement Errors in R PDF download
Iñaki Ucar, Edzer Pebesma and Arturo Azcorra

Abstract This paper presents an R package to handle and represent measurements with errors in a very simple way. We briefly introduce the main concepts of metrology and propagation of uncertainty, and discuss related R packages. Building upon this, we introduce the errors package, which provides a class for associating uncertainty metadata, automated propagation and reporting. Working with errors enables transparent, lightweight, less error-prone handling and convenient representation of measurements with errors. Finally, we discuss the advantages, limitations and future work of computing with errors.

Received: 2018-08-09; online 2018-12-13, supplementary material, (1.4 Kb)
CRAN packages: units, errors, car, msm, metRology, propagate, spup, distr, distrEllipse, distrEx, distrMod, distrRmetrics, distrSim, distrTeach, magrittr, ggplot2, tibble
CRAN Task Views implied by cited CRAN packages: Distributions, ChemPhys, Econometrics, Finance, Graphics, Multivariate, Phylogenetics, Robust, SocialSciences, Survival, WebTechnologies


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-075,
  author = {Iñaki Ucar and Edzer Pebesma and Arturo Azcorra},
  title = {{Measurement Errors in R}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-075},
  url = {https://journal.r-project.org/archive/2018/RJ-2018-075/index.html}
}