View source: R/spec_regarima.R
| add_outlier | R Documentation |
Generic function to add outliers or Ramp regressors (add_outlier() and
add_ramp()) to a specification or to remove them
(remove_outlier() and remove_ramp()).
add_outlier(x, type, date, name = sprintf("%s (%s)", type, date), coef = 0)
remove_outlier(x, type = NULL, date = NULL, name = NULL)
add_ramp(x, start, end, name = sprintf("rp.%s - %s", start, end), coef = 0)
remove_ramp(x, start = NULL, end = NULL, name = NULL)
x |
the specification to customize, must be a "SPEC" class object (see details). |
type, date |
type and date of the outliers. Possible |
name |
the name of the variable (to format print). |
coef |
the coefficient if needs to be fixed. If equal to 0 the outliers/ramps coefficients are estimated. |
start, end |
dates of the ramp regressor. |
x specification parameter must be a JD3_X13_SPEC" class object
generated with rjd3x13::x13_spec() (or "JD3_REGARIMA_SPEC" generated
with rjd3x13::spec_regarima() or "JD3_TRAMOSEATS_SPEC" generated with
rjd3tramoseats::spec_tramoseats() or "JD3_TRAMO_SPEC" generated with
rjd3tramoseats::spec_tramo()). If a Seasonal adjustment process is
performed, each type of Outlier will be allocated to a pre-defined component
after the decomposition: "AO" and "TC" to the irregular, "LS" and Ramps to
the trend.
The modified specification (with/without outliers or ramp)
More information on outliers and other auxiliary variables in JDemetra+ online documentation: https://jdemetra-new-documentation.netlify.app/
add_usrdefvar, intervention_variable
init_spec <- x13_spec_default
# Adding outlier on year 2012
new_spec <- add_outlier(init_spec, type = "AO", date = "2012-01-01")
# Removing outlier on year 2012
new_spec <- remove_outlier(new_spec, type = "AO", date = "2012-01-01")
# Adding ramp on year 2012
new_spec2 <- add_ramp(init_spec, start = "2012-01-01", end = "2012-12-01")
# Removing ramp on year 2012
new_spec2 <- remove_ramp(new_spec2, start = "2012-01-01", end = "2012-12-01")
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