plot.AMFCC_PhaseI | R Documentation |
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, ...)
x |
The output of either |
... |
Select the |
No return value, called for side effects.
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)
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