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rjd3x13

CRAN status Mentioned in Awesome Official Statistics

R-CMD-check lint

GH Pages built

rjd3x13 offers full access to options and outputs of X-13 (rjd3x13::x13()), including RegARIMA modelling (rjd3x13::regarima()) and X-11 decomposition (rjd3x13::x11()).

A specification can be created with rjd3x13::regarima_spec(), rjd3x13::x11_spec() or rjd3x13::x13_spec() and can be modified with the following functions:

Installation

Running rjd3 packages requires Java 17 or higher. How to set up such a configuration in R is explained here

Latest release

To get the current stable version (from the latest release):

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@*release")
remotes::install_github("rjdverse/rjd3x13@*release")
install.packages("rjd3x13", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Development version

You can install the development version of rjd3x13 from GitHub with:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3x13")

Usage

library("rjd3x13")

y <- rjd3toolkit::ABS$X0.2.09.10.M
x13_model <- x13(y)
summary(x13_model$result$preprocessing) # Summary of regarima model
#> Log-transformation: yes 
#> SARIMA model: (2,1,1) (0,1,1)
#> 
#> Coefficients
#>           Estimate Std. Error  T-stat Pr(>|t|)    
#> phi(1)     0.34740    0.06502   5.343 1.53e-07 ***
#> phi(2)     0.21733    0.06000   3.622 0.000329 ***
#> theta(1)  -0.69937    0.05115 -13.672  < 2e-16 ***
#> btheta(1) -0.48038    0.06993  -6.869 2.45e-11 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Regression model:
#>                   Estimate Std. Error T-stat Pr(>|t|)    
#> td               0.0023233  0.0006844  3.395 0.000755 ***
#> easter           0.0520113  0.0084894  6.127 2.14e-09 ***
#> TC (2000-06-01)  0.1590340  0.0288578  5.511 6.38e-08 ***
#> AO (2000-07-01) -0.2900774  0.0400551 -7.242 2.26e-12 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> Number of observations: 425, Number of effective observations: 412, Number of parameters: 9
#> Loglikelihood: 746.7517, Adjusted loglikelihood: -2120.875
#> Standard error of the regression (ML estimate): 0.03927991 
#> AIC: 4259.75, AICc: 4260.198, BIC: 4295.939

plot(x13_model) # Plot of the final decomposition

Package Maintenance and contributing

Any contribution is welcome and should be done through pull requests and/or issues. pull requests should include updated tests and updated documentation. If functionality is changed, docstrings should be added or updated.

Licensing

The code of this project is licensed under the European Union Public Licence (EUPL).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.