RoMFCC_PhaseII: Robust Multivariate Functional Control Charts - Phase II

In funcharts: Functional Control Charts

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)

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.

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

Author(s)

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

## Not run: 
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)

## End(Not run)

funcharts documentation built on April 3, 2025, 7:47 p.m.