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)

Arguments

calendars	list of calendars.
variables	list of variables.

Value

list of calendars and variables

References

More information on auxiliary variables in JDemetra+ online documentation: https://jdemetra-new-documentation.netlify.app/

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))

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

rjd3toolkit documentation built on Jan. 14, 2026, 1:06 a.m.