{rjd3tramoseats}

{rjd3tramoseats} offers full access to options and outputs of TRAMO-SEATS (rjd3tramoseats::tramoseats()), including TRAMO modelling (rjd3tramoseats::tramo()) and SEATS decomposition (rjd3tramoseats::seats_decompose()).

A specification can be created with rjd3tramoseats::tramo_spec() or rjd3tramoseats::tramoseats_spec() and modified with the following functions:

• for pre-processing: rjd3tramoseats::set_arima(), rjd3tramoseats::set_automodel(), rjd3tramoseats::set_basic(), rjd3tramoseats::set_easter(), rjd3tramoseats::set_estimate(), rjd3tramoseats::set_outlier(), rjd3tramoseats::set_tradingdays(), rjd3tramoseats::set_transform(), rjd3tramoseats::add_outlier(), rjd3tramoseats::remove_outlier(), rjd3tramoseats::add_ramp(), rjd3tramoseats::remove_ramp(), rjd3tramoseats::add_usrdefvar();

• for decomposition: rjd3tramoseats::set_seats();

• for benchmarking: rjd3toolkit::set_benchmarking().

Installation

Running rjd3 packages requires Java 21 or higher. How to set up such a configuration in R is explained here

🎉 {rjd3tramoseats} is now available on CRAN! 🎉

To install it, just launch the following command line:

install.packages("rjd3tramoseats")

To get the current development version of {rjd3tramoseats} from GitHub with:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3tramoseats")

Usage

Seasonal Adjustment with Tramo-Seats

library("rjd3tramoseats")
y <- rjd3toolkit::ABS$X0.2.09.10.M
ts_model <- tramoseats(y)
summary(ts_model$result$preprocessing) # Summary of tramo model
#> Log-transformation: yes 
#> SARIMA model: (0,1,1) (0,1,1)
#> 
#> Coefficients
#>           Estimate Std. Error  T-stat Pr(>|t|)    
#> theta(1)  -0.82783    0.02571 -32.196  < 2e-16 ***
#> btheta(1) -0.42554    0.06388  -6.661 9.01e-11 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Regression model:
#>                   Estimate Std. Error T-stat Pr(>|t|)    
#> mon             -0.0109446  0.0034805 -3.145 0.001788 ** 
#> tue              0.0048940  0.0035307  1.386 0.166481    
#> wed              0.0001761  0.0034970  0.050 0.959867    
#> thu              0.0132928  0.0035330  3.763 0.000193 ***
#> fri             -0.0024801  0.0035383 -0.701 0.483748    
#> sat              0.0153509  0.0035171  4.365 1.62e-05 ***
#> lp               0.0410667  0.0101178  4.059 5.94e-05 ***
#> easter           0.0503888  0.0072698  6.931 1.69e-11 ***
#> AO (2000-06-01)  0.1681662  0.0299743  5.610 3.78e-08 ***
#> AO (2000-07-01) -0.1972348  0.0298664 -6.604 1.28e-10 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> Number of observations: 425, Number of effective observations: 412, Number of parameters: 13
#> Loglikelihood: 781.358, Adjusted loglikelihood: -2086.269
#> Standard error of the regression (ML estimate): 0.03615788 
#> AIC: 4198.538, AICc: 4199.452, BIC: 4250.811
plot(ts_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).