v3.7.1

{rjd3toolkit} 3.7.1

Updates

Fixed

• Bug with to_tscollection() (moniker conversion)

Changed

• Use get_java_version() instead of current_java_version

v3.6.0

{rjd3toolkit} 3.6.0

Installation

Source version

From GitHub

To install this release automatically, you can use the code from the README:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@v3.6.0")

From R-Universe

install.packages("rjd3toolkit", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Updates

Changed

• default group value with mts objects in modelling_context #107
• Examples are executed only if Java version >= 17

Removed

• fct parameter in set_automodel() #85

Added

• get_java_version() function to compute the Java installed version
• current_java_version character string with the current installed Java version
• minimal_java_version character string with the minimum viable Java version for rjdverse
• get_date_min() to get the minimum date
• get_date_max() to get the maximum date
• New example to use the functions (#85)
• Documentation of bias argument in set_benchmarking()
• New datasets : Electricity (French national electricity consumtion), Births (Number of births registered in France from 1968 to 2024), x13_spec_default(Default X13 specification) and tramoseats_spec_default (Default Tramo-Seats specification)

v3.5.1

{rjd3toolkit} 3.5.1

Installation

Source version

From GitHub

To install this release automatically, you can use the code from the README:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@v3.5.1")

From R-Universe

install.packages("rjd3toolkit", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Updates

Changed

• New JARS

v3.5.0

{rjd3toolkit} 3.5.0

Installation

Source version

From GitHub

To install this release automatically, you can use the code from the README:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@v3.5.0")

From R-Universe

install.packages("rjd3toolkit", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Changed

• New JARS
• Replace . with _ in function's name #88
• The dataset retail is renamed Retail #89
• The number of regressor was false for TD3c #92

Added

• Spline functions (periodic, b-splines, cardinal splines)
• function .add_ud_var (from {rjd3tramoseats} and {rjd3x13})
• warning added in the function calendar_td #10
• Regressor TD2c for regarima specifications #53

v3.3.0

{rjd3toolkit} 3.3.0

Installation

Source version

From GitHub

To install this release automatically, you can use the code from the README:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@v3.3.0")

From R-Universe

install.packages("rjd3toolkit", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

From file

• Download the file rjd3toolkit_3.3.0.tar.gz
• Install with the command line:

install.packages("rjd3toolkit_3.3.0.tar.gz", repos = NULL, type = "source")

Binary versions

• Download the binary version of the package related to your R version (so the file rjd3toolkit_3.3.0_R_X.X.X.zip with X.X.X your version of R):

# For example with R 4.2.3
temp_path <- file.path(tempdir(), "rjd3toolkit_3.3.0.zip")
download.file(
    url = "https://github.com/rjdverse/rjd3toolkit/releases/download/v3.3.0/rjd3toolkit_3.3.0_R_4.2.3.zip",
    destfile = temp_path
)
install.packages(temp_path, repos = NULL, type = "binary")

Changed

• New JARS
• Improve Canova-Hansen tests for seasonality and trading days (new options, more output)
• Document (UC)ARIMA models

v3.2.4

rjd3toolkit 3.2.4

Installation

Source version

From GitHub

To install this release automatically, you can use the code from the README:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@v3.2.4")

From R-Universe

install.packages("rjd3toolkit", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

From file

• Download the file rjd3toolkit_3.2.4.tar.gz
• Install with the command line:

install.packages("rjd3toolkit_3.2.4.tar.gz", repos = NULL, type = "source")

Binary versions

• Download the binary version of the package related to your R version (so the file rjd3toolkit_3.2.4_R_X.X.X.zip with X.X.X your version of R):

# For example with R 4.2.3
temp_path <- file.path(tempdir(), "rjd3toolkit_3.2.4.zip")
download.file(
    url = "https://github.com/rjdverse/rjd3toolkit/releases/download/v3.2.4/rjd3toolkit_3.2.4_R_4.2.3.zip",
    destfile = temp_path
)
install.packages(temp_path, repos = NULL, type = "binary")

Updates

Fixed

• Correct SA decomposition with backcasts and forecasts (Java to R transfer) #2

Changed

• New .jar (related to release 3.2.4)
• Some linting of R functions

v3.2.2

Merge pull request #29 from rjdemetra/develop

v3.2.2

v3.2.1

Merge pull request #23 from rjdemetra/develop

v3.2.1

v3.2.0

Merge pull request #20 from rjdemetra/develop

v3.2.0

v3.1.0

Merge pull request #13 from rjdemetra/develop

v3.1.0