Builds an FPCA-based control chart from in-control functional data. The data is split into a tuning set (for FPCA) and a calibration set (for control limits). Computes Hotelling T-squared and SPE statistics.
Arguments
- fdataobj
An object of class
fdatacontaining in-control functional data (at least 4 observations).- ncomp
Number of principal components (default 5).
- alpha
Significance level for control limits (default 0.05).
- tuning.fraction
Fraction of data used for FPCA tuning (default 0.5).
- seed
Random seed for train/calibration split (default 42).
Value
An object of class spm.chart with components:
- eigenvalues
Eigenvalues from FPCA
- t2.phase1
T-squared values for calibration set
- spe.phase1
SPE values for calibration set
- t2.ucl
T-squared upper control limit
- spe.ucl
SPE upper control limit
- ncomp
Number of components used
- t2.description
Description of T-squared limit
- spe.description
Description of SPE limit
- fdataobj
Original fdata object
- .rust
Internal fields for Phase II monitoring
See also
spm.monitor for Phase II monitoring,
spm.ewma for EWMA-based monitoring,
frcc.phase1 for regression-adjusted monitoring
Examples
# \donttest{
# Simulate in-control functional data
set.seed(1)
n <- 50
m <- 30
argvals <- seq(0, 1, length.out = m)
X <- matrix(rnorm(n * m), n, m)
fd <- fdata(X, argvals = argvals)
# Build Phase I chart
chart <- spm.phase1(fd, ncomp = 3)
chart
#> SPM Control Chart (Phase I)
#> Components: 3
#> Alpha: 0.05
#> T2 UCL: 7.815
#> SPE UCL: 1.811
#> Observations: 50
#> Grid points: 30
#> Eigenvalues: 0.158, 0.122, 0.107
# }