plot.AMFCC_PhaseI function

Plot the results of the Phase I and the Phase II of the AMFCC

This function provides plots of either the monitoring statistics or the contribution plot for a given observation.

## S3 method for class 'AMFCC_PhaseI'
plot(x, ...)

## S3 method for class 'AMFCC_PhaseII'
plot(x, ...)

Arguments

• x: The output of either AMFCC_PhaseI or AMFCC_PhaseII.
• ...: Select the type of plot to produce either the contribution plot 'cont' or the monitoring plot 'mon'. Default is 'mon'. Select the combining_function to use for the monitoring plot either 'Fisher' or 'Tippett'. Default is 'Fisher'. Set the observation index ind_obs for which producing the contribution plot.

Returns

No return value, called for side effects.

Examples

library(funcharts)
N <- 10
l_grid <- 10
p <- 2
grid <- seq(0, 1, l = l_grid)

Xall_tra <- funcharts::simulate_mfd(
  nobs = N,
  p = p,
  ngrid = l_grid,
  correlation_type_x = c("Bessel", "Gaussian")
)
X_tra <-
  data.frame(
    x = c(Xall_tra$X_list[[1]], Xall_tra$X_list[[2]]),
    timeindex = rep(rep(1:l_grid, each = (N)), p),
    curve = rep(1:(N), l_grid * p),
    var = rep(1:p, each = l_grid * N)
  )

Xall_II <- funcharts::simulate_mfd(
  nobs = N,
  p = p,
  ngrid = l_grid,
  shift_type_x = list("A", "B"),
  d_x = c(10, 10),
  correlation_type_x = c("Bessel", "Gaussian")
)

X_II <-
  data.frame(
    x = c(Xall_II$X_list[[1]], Xall_II$X_list[[2]]),
    timeindex = rep(rep(1:l_grid, each = (N)), p),
    curve = rep(1:(N), l_grid * p),
    var = rep(1:p, each = l_grid * N)
  )

# AMFCC -------------------------------------------------------------------
print("AMFCC")

mod_phaseI_AMFCC <- AMFCC_PhaseI(
  data_tra = X_tra,
  data_tun =
    NULL,
  grid = grid,
  ncores = 1
)

mod_phaseII_AMFCC <- AMFCC_PhaseII(data = X_II,
mod_Phase_I = mod_phaseI_AMFCC,
ncores = 1)

plot(mod_phaseII_AMFCC)
plot(mod_phaseII_AMFCC,type='cont',ind_obs=1)