Monitor New Data Against FRCC Chart (Phase II)

Predicts the functional response from the FOSR model, computes residuals, and monitors them against the established FRCC chart.

Usage

frcc.monitor(chart, newdata, new.predictors)

Arguments

chart

An object of class frcc.chart from frcc.phase1.

newdata

An object of class fdata with new functional response.

new.predictors

A matrix of new scalar predictors (n_new x p).

Value

An object of class spm.monitor with components:

t2

T-squared values

spe

SPE values

t2.alarm

Logical: TRUE where T-squared exceeds UCL

spe.alarm

Logical: TRUE where SPE exceeds UCL

residual.scores

Residual FPC scores

t2.ucl

T-squared control limit

spe.ucl

SPE control limit

See also

frcc.phase1 for building the chart

Examples

# \donttest{
set.seed(1)
n <- 60; m <- 20
argvals <- seq(0, 1, length.out = m)
X_pred <- cbind(rnorm(n), rnorm(n))
Y <- matrix(rnorm(n * m), n, m)
fd <- fdata(Y, argvals = argvals)
chart <- frcc.phase1(fd, X_pred, ncomp = 3)

# Monitor new data
X_new <- cbind(rnorm(10), rnorm(10))
Y_new <- matrix(rnorm(10 * m) + 2, 10, m)
fd_new <- fdata(Y_new, argvals = argvals)
mon <- frcc.monitor(chart, fd_new, X_new)
mon
#> SPM Monitoring Result (Phase II)
#>   Observations: 10 
#>   T2 alarms: 6 of 10 (60%) 
#>   SPE alarms: 10 of 10 (100%) 
#>   T2 UCL: 7.815 
#>   SPE UCL: 1.075 
# }