Measurement Errors in R

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.

Iñaki Ucar , Edzer Pebesma , Arturo Azcorra

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at

CRAN packages used

units, errors, car, msm, metRology, propagate, spup, distr, distrEllipse, distrEx, distrMod, distrRmetrics, distrSim, distrTeach, magrittr, ggplot2, tibble

CRAN Task Views implied by cited packages

Distributions, ChemPhys, Econometrics, Finance, Graphics, Multivariate, Phylogenetics, Robust, SocialSciences, Survival, WebTechnologies


Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".


For attribution, please cite this work as

Ucar, et al., "The R Journal: Measurement Errors in R", The R Journal, 2018

BibTeX citation

  author = {Ucar, Iñaki and Pebesma, Edzer and Azcorra, Arturo},
  title = {The R Journal: Measurement Errors in R},
  journal = {The R Journal},
  year = {2018},
  note = {},
  doi = {10.32614/RJ-2018-075},
  volume = {10},
  issue = {2},
  issn = {2073-4859},
  pages = {549-557}