Plot multivariate functional object over the training data set
This function plots selected functions in a phase_II monitoring data set against the corresponding training data set to be compared.
plot_mon(cclist, fd_train, fd_test, print_id = FALSE)
cclist |
A |
fd_train |
An object of class |
fd_test |
An object of class |
print_id |
A logical value, if TRUE, it prints also the id of the observation in the title of the ggplot. |
A ggplot of the multivariate functional data.
In particular, the multivariate functional data given in
fd_train are plotted on
the background in gray, while the multivariate functional data given in
fd_test are
plotted on the foreground, the colour
of each curve is black or red depending on if that curve
was signal as anomalous by at least a contribution plot.
library(funcharts)
data("air")
air <- lapply(air, function(x) x[201:300, , drop = FALSE])
fun_covariates <- c("CO", "temperature")
mfdobj_x <- get_mfd_list(air[fun_covariates],
n_basis = 15,
lambda = 1e-2)
y <- rowMeans(air$NO2)
y1 <- y[1:60]
y2 <- y[91:100]
mfdobj_x1 <- mfdobj_x[1:60]
mfdobj_x_tuning <- mfdobj_x[61:90]
mfdobj_x2 <- mfdobj_x[91:100]
mod <- sof_pc(y1, mfdobj_x1)
cclist <- control_charts_sof_pc(mod = mod,
y_test = y2,
mfdobj_x_test = mfdobj_x2,
mfdobj_x_tuning = mfdobj_x_tuning)
plot_control_charts(cclist)
cont_plot(cclist, 3)
plot_mon(cclist, fd_train = mfdobj_x1, fd_test = mfdobj_x2[3])Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.