funcharts
The goal of funcharts is to provide control charts for the statistical
process monitoring of multivariate functional data densely observed on
one-dimensional intervals. The package is thoroughly illustrated in the
paper of Capezza et al. (2023). The package provides the methodologies
proposed in Colosimo and Pacella (2010), Capezza et al. (2020),
Centofanti et al. (2021), Capezza et al. (2024a), and Capezza et
al. (2024b). Moreover, this package provides a new class mfd for
multivariate functional data that is a wrapper of the class fd of the
package fda. See the
vignette("mfd", package = "funcharts").
In particular:
- Colosimo and Pacella (2010) propose control charts for monitoring
functional data based on functional principal component analysis.
vignette("colosimo2010", package = "funcharts") - Capezza et al. (2020) propose control charts for monitoring a scalar
response variable and functional covariates using scalar-on-function
regression. See the
vignette("capezza2020", package = "funcharts"). - Centofanti et al. (2021) propose the functional regression control
chart (FRCC), i.e. control charts for monitoring a functional response
variable conditionally on multivariate functional covariates. See the
vignette("centofanti2021", package = "funcharts"). - Capezza et al. (2024a) propose the adaptive multivariate functional EWMA (AMFEWMA) control chart.
- Capezza et al. (2024b) propose the robust multivariate functional control chart (RoMFCC).
- Centofanti et al. (2024) propose the functional real-time monitoring (FRTM) control chart.
Installation
You can install the CRAN version of the R package funcharts by doing:
install.packages("funcharts")You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("unina-sfere/funcharts")References
- Capezza C, Centofanti F, Lepore A, Menafoglio A, Palumbo B, Vantini S. (2023) funcharts: control charts for multivariate functional data in R. Journal of Quality Technology, <doi:10.1080/00224065.2023.2219012>.
- Capezza C, Lepore A, Menafoglio A, Palumbo B, Vantini S. (2020) Control charts for monitoring ship operating conditions and CO2 emissions based on scalar-on-function regression. Applied Stochastic Models in Business and Industry, 36(3):477–500, <doi:10.1002/asmb.2507>
- Capezza, C., Capizzi, G., Centofanti, F., Lepore, A., Palumbo, B. (2024a) An Adaptive Multivariate Functional EWMA Control Chart. To appear in Journal of Quality Technology, <doi:https://doi.org/10.1080/00224065.2024.2383674>.
- Capezza, C., Centofanti, F., Lepore, A., Palumbo, B. (2024b) Robust Multivariate Functional Control Charts. Technometrics, 66(4):531–547, <doi:10.1080/00401706.2024.2327346>.
- Centofanti F, Lepore A, Menafoglio A, Palumbo B, Vantini S. (2021) Functional Regression Control Chart. Technometrics, 63(3), 281–294, <doi:10.1080/00401706.2020.1753581>.
- Centofanti, F., A. Lepore, M. Kulahci, and M. P. Spooner (2024). Real-time monitoring of functional data. Accepted for publication in Journal of Quality Technology.
- Colosimo BM, Pacella, M. (2010) A comparison study of control charts for statistical monitoring of functional data. International Journal of Production Research, 48(6), 1575-1601, <doi:10.1080/00207540802662888>.