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Remove non-significant outliers from a JDemetra+ workspace

Source: R/modify-specification.R
remove_non_significant_outliers.Rd

This function scans a JDemetra+ workspace (.xml) and removes regression outliers whose p-values are above a given threshold. Both the estimation specification and the reference specification are updated accordingly, and the workspace file is saved in place.

Typical use case: after estimation with user pre-specified outliers, outliers with weak statistical significance (e.g. p > 0.3) are dropped to simplify the regression specification.

Usage

remove_non_significant_outliers(
  ws_path,
  threshold = 0.3,
  reference = FALSE,
  estimation = FALSE,
  verbose = TRUE
)

Arguments

ws_path

[character] Path to a JDemetra+ workspace file (usually with extension .xml).

threshold

[numeric] Maximum p-value for keeping an outlier. Outliers with Pr(>|t|) > threshold are removed. Default is 0.3.

reference

Boolean indicating if the reference specification should be modified.

estimation

Boolean indicating if the estimation specification should be modified.

verbose

Boolean indicating whether to print additional information. Default is TRUE.

Value

The function invisibly returns NULL, but it modifies the workspace file in place (saved at the same location as ws_path).

Details

The function:

  • iterates over all the series (SA-Items) in the workspace,

  • identifies outliers in the regarima specification,

  • checks their p-values in the pre-processing regression summary,

  • removes those with p-values above the threshold from both estimationSpec and, if present, referenceSpec,

  • saves the workspace file.

Examples


library("rjd3workspace")
library("rjd3x13")
library("rjd3toolkit")

# \donttest{
new_spec <- x13_spec() |>
    add_outlier(type = "LS", date = "1990-01-01")
jws <- create_ws_from_data(x = ABS[, 1, drop = FALSE], spec = new_spec)
path_ws <- tempfile(pattern = "ws", fileext = ".xml")
save_workspace(jws, file = path_ws)

# Remove non-significant outliers (p > 0.3) from a workspace
remove_non_significant_outliers(path_ws, threshold = 0.3, reference = TRUE)
#> 
#> 🏷 WS  ws1fde2c836815 
#> 📌 SAI n° 1 
#> 💾 Saving WS file
# }