Manage regression components in JDemetra+ workspaces — assign

These functions allow extracting, exporting, importing and assigning regression components used in JDemetra+ workspaces.

Usage

assign_outliers(jws, outliers, spec_type = NULL, verbose = TRUE)

assign_td(jws, td, spec_type = NULL, verbose = TRUE)

export_outliers(outliers, path = NULL, verbose = TRUE)

import_outliers(path, verbose = TRUE)

export_td(td, path = NULL, verbose = TRUE)

import_td(path, verbose = TRUE)

retrieve_outliers(jws, spec_type = NULL, verbose = TRUE)

retrieve_td(jws, spec_type = NULL, verbose = TRUE)

Arguments

jws: A Java Workspace object, as returned by rjd3workspace::jws_open() or rjd3workspace::jws_new().
outliers: [data.frame] A data.frame created with retrieve_outliers or import_outliers. See Format section for more information about the format of this argument.
spec_type: Character. Indicating the type of spec where the outliers whould be extracted. Accepted values : "Reference", "Estimation" or "Result".
verbose: Boolean indicating whether to print additional information. Default is TRUE.
td: [data.frame] A data.frame created by retrieve_td or import_td. See Format section for more information about the format of this argument.
path: character Path to a YAML file to read or write a table.

Value

retrieve_outliers() and import_outliers() returns data.frame representing the outliers.
retrieve_td() and import_td() returns data.frame representing the trading days variables
export_outliers() and export_td() functions invisibly return the path of the YAML file written.
assign_XXX() functions invisibly return the updated workspace jws.

Details

Two types of regression components are currently supported:

Outliers
Trading-day regressors (TD)

Format

Outliers table

Outliers are represented by a data.frame with three columns:

series : name of the series in the workspace.
name : name of the outlier (by default "type date").
type : type of the outlier (AO, LS, TC or SO).
date : date of the outlier in YYYY-MM-DD format.

These tables are typically created with retrieve_outliers() or import_outliers().

Trading-day table

Trading-day specifications are represented by a data.frame with two columns:

series : name of the series in the workspace.
regs : name of the trading-day regressor set to apply (e.g. REG1, REG2, ..., optionally with LY).

These tables are typically created with retrieve_td() or import_td().

Workflow

The workflow typically follows these steps:

Extract regression information from a workspace (retrieve_XXX())
Optionally export it to a YAML file (export_XXX())
Import it later from the YAML file (import_XXX())
Assign the regression specification to another workspace (assign_XXX())

Other

The assignment functions (assign_XXX()) modify the first SA-Processing of the workspace.

Currently, regression information can be extracted (retrieve_XXX()) from the resultSpec, estimationSpec or referenceSpec, while the assignment step (assign_XXX()) is performed in both the referenceSpec and the estimationSpec.

Examples


library("rjd3workspace")
library("rjd3toolkit")
# \donttest{
my_data <- ABS[, 1:3]
jws <- create_ws_from_data(my_data)
set_context(jws, create_insee_context(start = c(2015L, 1L)))

## Outliers

# Read all the outliers from a workspace
outs <- retrieve_outliers(jws, spec_type = "Result")
#> Série X0.2.09.10.M, 1/3
#> Série X0.2.08.10.M, 2/3
#> Série X0.2.07.10.M, 3/3

# Export outliers
path_outs <- tempfile(pattern = "outliers-table", fileext = ".yaml")
export_outliers(outs, path_outs)
#> The outliers table will be written at  /tmp/Rtmp6rSrQc/outliers-table1f3d4fb36621.yaml 

# Import outliers from a file
outs2 <- import_outliers(path_outs)
#> The outliers table will be read at  /tmp/Rtmp6rSrQc/outliers-table1f3d4fb36621.yaml 

# Assign the outliers to a WS
assign_outliers(jws = jws, outliers = outs2, spec_type = "Reference")
#> Série X0.2.09.10.M, 1/3
#> Série X0.2.08.10.M, 2/3
#> Série X0.2.07.10.M, 3/3


## Trading day workflow

# Read all the td variables from a workspace
td <- retrieve_td(jws, spec_type = "Estimation")
#> Série X0.2.09.10.M, 1/3
#> Série X0.2.08.10.M, 2/3
#> Série X0.2.07.10.M, 3/3

# Export td variables
path_td <- tempfile(pattern = "td-table", fileext = ".yaml")
export_td(td, path_td)
#> The td table will be written at /tmp/Rtmp6rSrQc/td-table1f3d1d469f57.yaml 

# Import td variable from a file
td2 <- import_td(path_td)
#> The td table will be read at  /tmp/Rtmp6rSrQc/td-table1f3d1d469f57.yaml 

# Select td
td3 <- select_td(my_data)
#> 
#> Série X0.2.09.10.M en cours... 1/3 
#> Computing spec No_TD ...Done !
#> Computing spec REG1 ...Done !
#> Computing spec REG2 ...Done !
#> Computing spec REG3 ...Done !
#> Computing spec REG5 ...Done !
#> Computing spec REG6 ...Done !
#> Computing spec LY ...Done !
#> Computing spec REG1_LY ...Done !
#> Computing spec REG2_LY ...Done !
#> Computing spec REG3_LY ...Done !
#> Computing spec REG5_LY ...Done !
#> Computing spec REG6_LY ...Done !
#> 
#> Série X0.2.08.10.M en cours... 2/3 
#> Computing spec No_TD ...Done !
#> Computing spec REG1 ...Done !
#> Computing spec REG2 ...Done !
#> Computing spec REG3 ...Done !
#> Computing spec REG5 ...Done !
#> Computing spec REG6 ...Done !
#> Computing spec LY ...Done !
#> Computing spec REG1_LY ...Done !
#> Computing spec REG2_LY ...Done !
#> Computing spec REG3_LY ...Done !
#> Computing spec REG5_LY ...Done !
#> Computing spec REG6_LY ...Done !
#> 
#> Série X0.2.07.10.M en cours... 3/3 
#> Computing spec No_TD ...Done !
#> Computing spec REG1 ...Done !
#> Computing spec REG2 ...Done !
#> Computing spec REG3 ...Done !
#> Computing spec REG5 ...Done !
#> Computing spec REG6 ...Done !
#> Computing spec LY ...Done !
#> Computing spec REG1_LY ...Done !
#> Computing spec REG2_LY ...Done !
#> Computing spec REG3_LY ...Done !
#> Computing spec REG5_LY ...Done !
#> Computing spec REG6_LY ...Done !

# Assign the td variables to a WS
assign_td(jws = jws, td = td3, spec_type = "Estimation")
#> Série X0.2.09.10.M, 1/3
#> Série X0.2.08.10.M, 2/3
#> Série X0.2.07.10.M, 3/3
# }