modelling_context: Create modelling context

In rjd3toolkit: Utility Functions Around 'JDemetra+ 3.0'

Create modelling context

Description

Function allowing to include calendars and external regressors in a format that makes them usable in an estimation process (Reg-ARIMA or Tramo modelling, stand alone or as pre-processing in seasonal adjustment). The regressors can be created with functions available in the package or come from any other source, provided they are ts class objects.

Usage

modelling_context(calendars = NULL, variables = NULL, verbose = TRUE)

Arguments

calendars	list of calendars.
variables	list of variables.
verbose	Boolean indicating whether to print additional information. Default is TRUE.

Value

list of calendars and variables

References

More information on auxiliary variables in JDemetra+ online documentation: https://doc.jdemetra.org/a-outlier-detection

See Also

add_usrdefvar, intervention_variable

Examples

# Creating one or several external regressors (TS objects), which will
# be gathered in one or several groups
iv1 <- intervention_variable(12, c(2000, 1), 60,
    starts = "2001-01-01", ends = "2001-12-01"
)
iv2 <- intervention_variable(12, c(2000, 1), 60,
    starts = "2001-01-01", ends = "2001-12-01", delta = 1
)

# Regressors as a list of two groups reg1 and reg2
vars <- list(reg1 = list(x = iv1), reg2 = list(x = iv2), reg3 = ABS)

# Creating the modelling context
my_context <- modelling_context(variables = vars)

rjd3toolkit documentation built on Sept. 21, 2026, 5:06 p.m.