shewhartr: Statistical Process Control with Tidyverse-Native Workflows
A comprehensive toolkit for Statistical Process Control (SPC)
that combines the rigor of classical Shewhart methodology with modern
tidyverse-native interfaces. Provides classical control charts for
variables (I-MR, Xbar-R, Xbar-S) and attributes (p, np, c, u), as
well as regression-based control charts for processes with trend.
Includes Nelson runs tests, Average Run Length (ARL) simulation,
process capability indices with bootstrap confidence intervals,
Box-Cox transformation guidance, and a clean Phase I / Phase II
workflow. All chart objects integrate with broom via 'tidy',
'glance' and 'augment' methods. References: Shewhart (1931,
ISBN:0-87389-076-0); Montgomery (2019, ISBN:978-1-119-39930-8);
Nelson (1984) <doi:10.1080/00224065.1984.11978921>; Woodall (2000)
<doi:10.1080/00224065.2000.11980013>; Box & Cox (1964)
<doi:10.1111/j.2517-6161.1964.tb00553.x>.
| Version: |
1.4.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
rlang (≥ 1.1.0), cli (≥ 3.6.0), dplyr (≥ 1.1.0), purrr (≥
1.0.0), tibble (≥ 3.2.0), tidyselect (≥ 1.2.0), ggplot2 (≥
3.5.0), broom (≥ 1.0.0), slider (≥ 0.3.0), grid, grDevices, stats, utils |
| Suggests: |
patchwork (≥ 1.1.0), plotly (≥ 4.10.0), qcc (≥ 2.7), testthat (≥ 3.2.0), knitr, rmarkdown, pkgdown, MASS |
| Published: |
2026-09-25 |
| DOI: |
10.32614/CRAN.package.shewhartr |
| Author: |
André Leite [aut, cre],
Hugo Vasconcelos [aut],
Raydonal Ospina [aut],
Cristiano Ferraz [aut],
Castlab [cph, fnd] |
| Maintainer: |
André Leite <leite at castlab.org> |
| BugReports: |
https://github.com/castlaboratory/shewhartr/issues |
| License: |
GPL-3 |
| URL: |
https://castlaboratory.github.io/shewhartr/,
https://github.com/castlaboratory/shewhartr |
| NeedsCompilation: |
no |
| Citation: |
shewhartr citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
shewhartr results |
Documentation:
| Reference manual: |
shewhartr.html , shewhartr.pdf
|
| Vignettes: |
ARL by Monte Carlo simulation (source, R code)
Reproducing the charts of Ferraz et al. (2020) (source, R code)
Attributes charts: p, np, c, u (source, R code)
Choosing a transformation: Box-Cox in practice (source, R code)
Case study: epidemiological monitoring (COVID-19, Recife) (source, R code)
Residual diagnostics, Tukey style (source, R code)
Getting started with shewhartr (source, R code)
Memory-based charts: EWMA and CUSUM (source, R code)
Multivariate charts: Hotelling T² (source, R code)
Phase I and Phase II (source, R code)
Simulating prospective monitoring with the seven-point rule (source, R code)
Regression-based control charts (source, R code)
Variables charts: I-MR, Xbar-R, Xbar-S (source, R code)
|
Downloads:
Reverse dependencies:
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