funcharts (version 1.7.0)

RoMFCC_PhaseII: Robust Multivariate Functional Control Charts - Phase II

Description

It calculates the Hotelling's and SPE monitoring statistics needed to plot the Robust Multivariate Functional Control Chart in Phase II.

Usage

RoMFCC_PhaseII(mfdobj_new, mod_phase1)

Value

A data.frame with as many rows as the number of multivariate functional observations in the phase II data set and the following columns:

• one id column identifying the multivariate functional observation in the phase II data set,

• one T2 column containing the Hotelling T2 statistic calculated for all observations,

• one column per each functional variable, containing its contribution to the T2 statistic,

• one spe column containing the SPE statistic calculated for all observations,

• T2_lim gives the upper control limit of the Hotelling's T2 control chart,

• spe_lim gives the upper control limit of the SPE control chart

Arguments

mfdobj_new

A multivariate functional data object of class mfd, containing the Phase II observations to be monitored.

mod_phase1

Output obtained by applying the function RoMFCC_PhaseI to perform Phase I. See RoMFCC_PhaseI.

Author

C. Capezza, F. Centofanti

References

Capezza, C., Centofanti, F., Lepore, A., Palumbo, B. (2024) Robust Multivariate Functional Control Chart. Technometrics, 66(4):531--547, doi:10.1080/00401706.2024.2327346.

Examples

if (FALSE) {
library(funcharts)
mfdobj <- get_mfd_list(air, n_basis = 5)
nobs <- dim(mfdobj$coefs)[2]
set.seed(0)
ids <- sample(1:nobs)
mfdobj1 <- mfdobj[ids[1:100]]
mfdobj_tuning <- mfdobj[ids[101:300]]
mfdobj2 <- mfdobj[ids[-(1:300)]]
mod_phase1 <- RoMFCC_PhaseI(mfdobj = mfdobj1,
                            mfdobj_tuning = mfdobj_tuning)
phase2 <- RoMFCC_PhaseII(mfdobj_new = mfdobj2,
                         mod_phase1 = mod_phase1)
plot_control_charts(phase2)
}