| PH1XBAR-package {PH1XBAR} | R Documentation |
PH1XBAR: Phase I Shewhart X-Bar Chart
Description
The purpose of 'PH1XBAR' is to build a Phase I Shewhart control chart for the basic Shewhart, the variance components and the ARMA models in R for subgrouped and individual data. More details can be found: Yao and Chakraborti (2020) doi: 10.1002/qre.2793, Yao and Chakraborti (2021) doi: 10.1080/08982112.2021.1878220, and Yao et al. (2023) doi: 10.1080/00224065.2022.2139783.
The utility of this package is in building a Shewhart-type control chart based on new methods for subgrouped and individual data. The Phase I chart is based on the multivariate normal/t or ARMA process.
Author(s)
Maintainer: Yuhui Yao yyao17@ua.edu
Other contributors:
Subha Chakraborti schakrab@cba.ua.edu [contributor]
Tyler Thomas tjthomas7@crimson.ua.edu [contributor]
Jason Parton jmparton@cba.ua.edu [contributor]
Xin Yang xyang15@cba.ua.edu [contributor]
References
Champ, C.W., and Jones, L.A. (2004) Designing Phase I X-bar charts with small sample sizes. Quality and Reliability Engineering International. 20(5), 497-510
Yao, Y., Hilton, C.W., and Chakraborti, S. (2017) Designing Phase I Shewhart X-bar charts: Extended tables and software. Quality and Reliability Engineering International. 33(8), 2667-2672.
Yao, Y., and Chakraborti, S. (2021). Phase I monitoring of individual normal data: Design and implementation. Quality Engineering, 33(3), 443-456.
Yao, Y., and Chakraborti, S. (2021). Phase I process monitoring: The case of the balanced one-way random effects model. Quality and Reliability Engineering International, 37(3), 1244-1265.
Yao, Y., Chakraborti, S., Yang, X., Parton, J., Lewis Jr, D., and Hudnall, M. (2023). Phase I control chart for individual autocorrelated data: application to prescription opioid monitoring. Journal of Quality Technology, 55(3), 302-317.
See Also
Useful links:
Examples
#Build a Phase I basic Shewhart control chart
data(grinder_data)
PH1XBAR(grinder_data, nsim=10)
# Build a Phase I individual control chart with an ARMA model
data(preston_data)
PH1ARMA(preston_data, nsim.process=10, nsim.coefs=10)