Real-time scalar-on-function regression control charts

This function is deprecated. Use regr_cc_sof_real_time. This function produces a list of data frames, each of them is produced by control_charts_sof_pc and is needed to plot control charts for monitoring in real time a scalar quality characteristic adjusted for by the effect of multivariate functional covariates.

control_charts_sof_pc_real_time(
  mod_list,
  y_test,
  mfdobj_x_test,
  mfdobj_x_tuning = NULL,
  alpha = list(T2 = 0.0125, spe = 0.0125, y = 0.025),
  limits = "standard",
  seed,
  nfold = NULL,
  ncores = 1
)

Arguments

mod_list

A list of lists produced by sof_pc_real_time, containing a list of scalar-on-function linear regression models estimated on functional data each evolving up to an intermediate domain point.

y_test

A numeric vector containing the observations of the scalar response variable in the phase II monitoring data set.

mfdobj_x_test

A list created using get_mfd_df_real_time or get_mfd_list_real_time, denoting a list of functional data objects in the phase II monitoring data set, each evolving up to an intermediate domain point, with observations of the multivariate functional covariates. The length of this list and mod_list must be equal, and their elements in the same position in the list must correspond to the same intermediate domain point.

mfdobj_x_tuning

A list created using get_mfd_df_real_time or get_mfd_list_real_time, denoting a list of functional data objects in the tuning data set (used to estimate control chart limits), each evolving up to an intermediate domain point, with observations of the multivariate functional covariates. The length of this list and mod_list must be equal, and their elements in the same position in the list must correspond to the same intermediate domain point. If NULL, the training data, i.e. the functional covariates in mod_list, are also used as the tuning data set. Default is NULL.

alpha

See control_charts_sof_pc.

limits

See control_charts_sof_pc.

seed

Deprecated: see control_charts_sof_pc.

nfold

See control_charts_sof_pc.

ncores

If you want parallelization, give the number of cores/threads to be used when creating objects separately for different instants.

Value

A list of data.frames each produced by control_charts_sof_pc, corresponding to a given instant.

See also

sof_pc_real_time, control_charts_sof_pc

Examples

if (FALSE) {
library(funcharts)
data("air")
air1 <- lapply(air, function(x) x[1:8, , drop = FALSE])
air2 <- lapply(air, function(x) x[9:10, , drop = FALSE])
mfdobj_x1_list <- get_mfd_list_real_time(air1[c("CO", "temperature")],
                                         n_basis = 15,
                                         lambda = 1e-2,
                                         k_seq = c(0.5, 1))
mfdobj_x2_list <- get_mfd_list_real_time(air2[c("CO", "temperature")],
                                         n_basis = 15,
                                         lambda = 1e-2,
                                         k_seq = c(0.5, 1))
y1 <- rowMeans(air1$NO2)
y2 <- rowMeans(air2$NO2)
mod_list <- sof_pc_real_time(y1, mfdobj_x1_list)
cclist <- control_charts_sof_pc_real_time(
  mod_list = mod_list,
  y_test = y2,
  mfdobj_x_test = mfdobj_x2_list)
plot_control_charts_real_time(cclist, 1)
}