- object
A list obtained as output from sof_pc,
i.e. a fitted scalar-on-function linear regression model.
- y_new
A numeric vector containing the observations of
the scalar response variable
in the phase II data set.
- mfdobj_x_new
An object of class mfd containing
the phase II data set of the functional covariates observations.
- y_tuning
A numeric vector containing the observations of the scalar response
variable in the tuning data set.
If NULL, the training data, i.e. the data used to
fit the scalar-on-function regression model,
are also used as the tuning data set.
Default is NULL.
- mfdobj_x_tuning
An object of class mfd containing
the tuning set of the multivariate functional data, used to estimate the
control chart limits.
If NULL, the training data, i.e. the data used to
fit the scalar-on-function regression model,
are also used as the tuning data set.
Default is NULL.
- alpha
If it is a number between 0 and 1,
it defines the overall type-I error probability.
If include_covariates is TRUE, i.e.,
also the Hotelling's T2 and SPE control charts are built
on the functional covariates, then the Bonferroni
correction is applied by setting the type-I error probability
in the three control charts equal to alpha/3.
In this last case,
if you want to set manually the Type-I error probabilities,
then the argument alpha must be a named list
with three elements, named T2, spe and y,
respectively, each containing
the desired Type I error probability of
the corresponding control chart, where y refers to the
regression control chart.
Default value is 0.05.
- parametric_limits
If TRUE, the limits are calculated based on the normal distribution
assumption on the response variable, as in Capezza et al. (2020).
If FALSE, the limits are calculated nonparametrically as
empirical quantiles of the distribution of the residuals calculated
on the tuning data set.
The default value is FALSE.
- include_covariates
If TRUE, also functional covariates are monitored through
control_charts_pca,.
If FALSE, only the scalar response, conditionally on the covariates,
is monitored.
- absolute_error
A logical value that, if include_covariates is TRUE, is passed
to control_charts_pca.