Package 'rjd3workspace'

Title: Interface to 'JDemetra+ 3.x' time series analysis software.
Description: R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>). It offers several functions to manipulate 'JDemetra+' workspaces, which can be read by the software and can store several seasonal adjusted series along with user-defined calendars or regression variables.
Authors: Jean Palate [aut], Alain Quartier-la-Tente [aut] , Tanguy Barthelemy [aut, cre, art], Anna Smyk [aut]
Maintainer: Tanguy Barthelemy <[email protected]>
License: EUPL
Version: 3.2.3.9000
Built: 2024-09-10 05:25:47 UTC
Source: https://github.com/rjdverse/rjd3workspace

Help Index


Extract Java Metadata

Description

Extract specific metadata or time series metadata of a SAItem.

Usage

.jsa_metadata(jsa, key)

.jsa_ts_metadata(jsa, key)

Arguments

jsa

Java SAItem object.

key

key of the metadata.


Read SAItem

Description

.jsa_results() extracts specific variables of the model of the SAItem while .jsa_read() extracts all the informations of a SAItem (see details).

Usage

.jsa_read(jsa)

.jsa_results(jsa, items = NULL)

Arguments

jsa

Java SAItem object.

items

vector of characters containing the variables to extract. See rjd3x13::x13_dictionary() or rjd3tramoseats::tramoseats_dictionary(). By default, extracts all the possible variables.

Details

A SAItem contains more information than just the results of a model. All those informations are extracted with the .jsa_read() function that returns a list with 5 objects:

  • ts: the raw time series.

  • domainSpec: initial specification. Reference for any relaxing of some elements of the specification.

  • estimationSpec: specification used for the current estimation.

  • pointSpec: specification corresponding to the results of the current estimation (fully identified model).

  • results: the result of the model.


Get the name of a SAProcessing or a SaItem

Description

Functions to retrieve the name of a SAProcessing (.jsap_name()) or SaItem (.jsa_name()).

This function is used to retrieve the Java names of all the sa_items contained in a SA-Processing.

Usage

.jsa_name(jsa)

.jsap_name(jsap)

.jsap_sa_name(jsap)

Arguments

jsap, jsa

the object to retrieve the name from.

jsap

the java object representing the SA-Processing

Value

A vector character.

See Also

Other functions to retrieve the name of JDemetra+ objects (workspace, SA-Processing or sa-item): .jsa_name, .jsap_name.

Examples

y <- rjd3toolkit::ABS$X0.2.09.10.M

jws <- .jws_new()
jsap1 <- .jws_sap_new(jws, "sa1")

add_sa_item(jsap1, name = "x13", x = rjd3x13::x13(y))
add_sa_item(jsap1, name = "tramo", x = rjd3tramoseats::tramoseats(y))
add_sa_item(jsap1, name = "x13-2", x = y, rjd3x13::x13_spec())
add_sa_item(jsap1, name = "tramo-2", x = y, rjd3tramoseats::tramoseats_spec())

print(.jsap_sa_name(jsap1))

Create a workspace or a multi-processing

Description

Functions to create a 'JDemetra+' workspace (.jws_new()) and to add a new multi-processing (.jws_sap_new()).

Usage

.jws_new(modelling_context = NULL)

.jws_sap_new(jws, name)

Arguments

modelling_context

The context (from rjd3toolkit::modelling_context()).

jws

A workspace object.

name

Character name of the new SAProcessing.

Examples

# To create an empty 'JDemetra+' workspace
jwk <- .jws_new()
jsap <- .jws_sap_new(jwk, "sa1")

Load a 'JDemetra+' workpace

Description

.jws_open() loads a workspace and .jws_compute() computes it (to be able to get all the models).

Usage

.jws_open(file)

.jws_load(file)

Arguments

file

the path to the 'JDemetra+' workspace to load. By default a dialog box opens.

See Also

read_workspace() to import all the models of a workspace.


Extract a SAProcessing or a SaItem

Description

Extract a SAProcessing or a SaItem

Usage

.jsap_sa(jsap, idx)

.jws_sap(jws, idx)

Arguments

idx

index of the object to extract.

jws, jsap

the workspace or the SAProcessing.


Count the number of objects inside a workspace or SAProcessing

Description

Functions to count the number of SAProcessing inside a workspace (jws_sap_count) or the number of SaItem inside a SAProcessing (jsap_sa_count).

Usage

.jsap_sa_count(jsap)

.jws_sap_count(jws)

Arguments

jws, jsap

the workspace or the SAProcessing.


Add Calendar to Workspace

Description

Add Calendar to Workspace

Usage

add_calendar(jws, name, calendar)

Arguments

jws

A workspace object.

name

the name of the calendar to add.

calendar

the calendar to add.


Add SAItem to SAProcessing

Description

Add SAItem to SAProcessing

Usage

add_sa_item(jsap, name, x, spec, ...)

Arguments

jsap

the SAProcessing.

name

the name of SAItem.

x

either a seasonal adjustment model (from rjd3x13::x13() or rjd3tramoseats::tramoseats()), a SaItem or a "ts" object.

spec

the specification to use when x is a "ts" object.

...

other unused parameters.

Examples

dir <- tempdir()
y <- rjd3toolkit::ABS$X0.2.09.10.M
jws <- .jws_new()
jsap1 <- .jws_sap_new(jws, "sa1")
add_sa_item(jsap1, name = "x13", x = rjd3x13::x13(y))
add_sa_item(jsap1, name = "tramo", x = rjd3tramoseats::tramoseats(y))
add_sa_item(jsap1, name = "x13-2", x = y, rjd3x13::x13_spec())
add_sa_item(jsap1, name = "tramo-2", x = y, rjd3tramoseats::tramoseats_spec())
save_workspace(jws, file.path(dir, "workspace.xml"))

Add Variable to Workspace

Description

Add Variable to Workspace

Usage

add_variable(jws, group, name, y)

Arguments

jws

A workspace object.

group, name

the group and the name of the variable to add.

y

the variable (a ts object).


Deprecated functions

Description

Deprecated functions

Usage

.jmp_sa_count(jmp)

.jmp_name(jmp)

.jmp_sa(jmp, idx)

.jmp_sa_name(jmp)

.jmp_load(jmp)

.jws_multiprocessing(jws, idx)

.jws_multiprocessing_new(jws, name)

.jws_multiprocessing_count(jws)

Arguments

jmp, idx, jws, name

Parameters.


Get Context from Workspace

Description

Get Context from Workspace

Usage

get_context(jws)

Arguments

jws

the workspace.


Copy Workspace or a SAProcessing

Description

Copy Workspace or a SAProcessing

Usage

.jsap_make_copy(jsap)

.jws_make_copy(jws)

Arguments

jws, jsap

Java Workspace or Multiprocessing


Title

Description

Title

Usage

read_calendars(file)

Arguments

file

Title

Description

Title

Usage

read_variables(file)

Arguments

file

Read all SaItems

Description

Functions to read all the SAItem of a SAProcessing (read_sap()) or a workspace (read_workspace()).

Usage

read_sap(jsap)

read_workspace(jws, compute = TRUE)

Arguments

jsap

Java SAProcessing.

jws

Java workspace.

compute

Compute the workspace.

Examples

file<-system.file("workspaces", "test.xml", package = "rjd3workspace")
jws<-.jws_load(file)
# We don't compute the workspace
rws<-read_workspace(jws, FALSE)

Refresh Workspace or SAProcessing

Description

Refresh Workspace or SAProcessing

Usage

.jsap_refresh(
  jsap,
  policy = c("FreeParameters", "Complete", "Outliers_StochasticComponent", "Outliers",
    "FixedParameters", "FixedAutoRegressiveParameters", "Fixed"),
  period = 0,
  start = NULL,
  end = NULL,
  info = c("All", "Data", "None")
)

.jws_refresh(
  jws,
  policy = c("FreeParameters", "Complete", "Outliers_StochasticComponent", "Outliers",
    "FixedParameters", "FixedAutoRegressiveParameters", "Fixed"),
  period = 0,
  start = NULL,
  end = NULL,
  info = c("All", "Data", "None")
)

Arguments

policy

the refresh policy to apply (see details).

period, start, end

to specify the span on which outliers will not be re-identified (i.e.: re-detected) when policy = "Outliers" or policy = "Outliers_StochasticComponent". Span definition: period: numeric, number of observations in a year (12, 4...). start and end: first and last date from which outliers will not be re-identfied, defined as arrays of two elements: year and first period (for example, if period = 12, c(1980, 1) for January 1980). If they are not specified, the outliers will be re-identified on the whole series.

info

information to refresh.

jws, jsap

Java Workspace or Multiprocessing

Details

Available refresh policies are:

Current: applying the current pre-adjustment reg-arima model and adding the new raw data points as Additive Outliers (defined as new intervention variables)

Fixed: applying the current pre-adjustment reg-arima model and replacing forecasts by new raw data points.

FixedParameters: pre-adjustment reg-arima model is partially modified: regression coefficients will be re-estimated but regression variables, Arima orders and coefficients are unchanged.

FixedAutoRegressiveParameters: same as FixedParameters but Arima Moving Average coefficients (MA) are also re-estimated, Auto-regressive (AR) coefficients are kept fixed.

FreeParameters: all regression and Arima model coefficients are re-estimated, regression variables and Arima orders are kept fixed.

Outliers: regression variables and Arima orders are kept fixed, but outliers will be re-detected on the defined span, thus all regression and Arima model coefficients are re-estimated

Outliers_StochasticComponent: same as "Outliers" but Arima model orders (p,d,q)(P,D,Q) can also be re-identified.


Title

Description

Title

Usage

regarima_read_spec(file)

Arguments

file

Title

Description

Title

Usage

regarima_write_spec(spec, file)

Arguments

file

Replace or Remove a SaItem

Description

replace_sa_item() replaces a SaItem of a SAProcessing and remove_sa_item() removes a SaItem from a SAProcessing

This functions clear a SA-Processing by removing all the sa-item contained.

Usage

replace_sa_item(jsap, idx, jsa)

remove_sa_item(jsap, idx)

remove_all_sa_item(jsap)

transfer_series(jsap_from, jsap_to, selected_series, print_indications = TRUE)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

jsa

the new SaItem.

jsap_from

The SA-Processing from which to take the series

jsap_to

The SA-Processing in which to paste the series

selected_series

The vector containing the series-to-update's names.

print_indications

A boolean to print indications on the processing status (optional)

Details

If selected_series is missing, all series from jsap_from will be copied. In this context, the word series refers to sa-item.

Value

NULL returned invisibly

NULL returned invisibly


Save Workspace

Description

Save Workspace

Usage

save_workspace(jws, file, replace = FALSE)

Arguments

jws

the workspace object to export.

file

the path where to export the 'JDemetra+' workspace (.xml file).

replace

boolean indicating if the workspace should be replaced if it already exists.

Examples

dir <- tempdir()
jws <- .jws_new()
jsap1 <- .jws_sap_new(jws, "sa1")
y <- rjd3toolkit::ABS$X0.2.09.10.M
add_sa_item(jsap1, name = "x13", x = y, rjd3x13::x13_spec())
save_workspace(jws, file.path(dir, "workspace.xml"))

Get/Set SaItem Comment

Description

Get/Set SaItem Comment

Usage

set_comment(jsap, idx, comment)

get_comment(jsa)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

comment

character containing the comment.

jsa

a SaItem.


Set Context of a Workspace

Description

Set Context of a Workspace

Usage

set_context(jws, modelling_context = NULL)

Arguments

jws

A workspace object.

modelling_context

The context (from rjd3toolkit::modelling_context()).


Set the name associated to a SaItem Comment

Description

Set the name associated to a SaItem Comment

Usage

set_name(jsap, idx, name)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

name

character containing the name of the SAItem.

See Also

.jsa_name()


Get/Set SaItem Priority

Description

Get/Set SaItem Priority

Usage

set_priority(jsap, idx, priority = 0)

get_priority(jsa)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

priority

integer containing the priority.

jsa

a SaItem.


Get/Set the Raw Data of a SaItem

Description

Get/Set the Raw Data of a SaItem

Usage

set_raw_data(jsap, idx, y)

get_raw_data(jsa)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

y

the new raw time serie.

jsa

a SaItem.


Set Specification or Data of a SaItem

Description

Set Specification or Data of a SaItem

Usage

set_specification(jsap, idx, spec)

set_domain_specification(jsap, idx, spec)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

spec

the new specification.


Get/Set the time series of a SaItem

Description

Get/Set the time series of a SaItem

Usage

set_ts(jsap, idx, y)

get_ts(jsa)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

y

a "full" time series (jd3-like).

jsa

a SaItem.


Set Time Series Metadata of a SaItem

Description

Function to set the time series metadata of a SaItem (provider, source of the data...). set_ts_metadata() uses the metadata of another SaItem while put_ts_metadata() allows to update a specific key with a new information.

Usage

set_ts_metadata(jsap, idx, ref_jsa)

put_ts_metadata(jsap, idx, key, value)

Arguments

jsap

the SAProcessing to modify.

idx

index of the target SaItem.

ref_jsa

a reference SaItem containing the metadata.

key

key of the metadata.

value

value of the metadata.

Examples

# Change the file of a given item
file <- system.file("workspaces", "test.xml", package = "rjd3workspace")
jws <- .jws_load(file)
jsap <- .jws_sap(jws, 1)
jsa <- .jsap_sa(jsap, 1)
nid <- rjd3providers::spreadsheet_change_file(.jsa_ts_metadata(jsa, "@id"), "test.xlsx")
put_ts_metadata(jsap, 1, "@id", nid)
jsa <- .jsap_sa(jsap, 1)
.jsa_ts_metadata(jsa, "@id")

Title

Description

Title

Usage

tramo_read_spec(file)

Arguments

file

Title

Description

Title

Usage

tramo_write_spec(spec, file)

Arguments

file

Title

Description

Title

Usage

tramoseats_read_spec(file)

Arguments

file

Title

Description

Title

Usage

tramoseats_write_spec(spec, file)

Arguments

file

Title

Description

Title

Usage

write_calendars(calendars, file)

Arguments

file

Title

Description

Title

Usage

write_variables(vars, file)

Arguments

file

Title

Description

Title

Usage

x13_read_spec(file)

Arguments

file

Title

Description

Title

Usage

x13_write_spec(spec, file)

Arguments

file