The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC (qcc, MSQC), qcr provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, \(\bar{x}\), \(S\), \(R\), \(p\), \(np\), \(c\), \(u\), EWMA, and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T\(^2\), MEWMA and MCUSUM. As representative features, multivariate nonparametric alternatives based on data depth are implemented in this package: \(r\), \(Q\) and \(S\) control charts. The qcr library also estimates the most complete set of capability indices from first to the fourth generation, covering the nonparametric alternatives, and performing the corresponding capability analysis graphical outputs, including the process capability plots. Moreover, Phase I and II control charts for functional data are included.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2021-034.zip
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For attribution, please cite this work as
Flores, et al., "Statistical Quality Control with the qcr Package", The R Journal, 2021
BibTeX citation
@article{RJ-2021-034,
author = {Flores, Miguel and Fernández-Casal, Rubén and Naya, Salvador and Tarrío-Saavedra, Javier},
title = {Statistical Quality Control with the qcr Package},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-034},
doi = {10.32614/RJ-2021-034},
volume = {13},
issue = {1},
issn = {2073-4859},
pages = {194-217}
}