rjd3x13 offers full acces to options and outputs of X-13-Arima
(rjd3x13::x13()), including RegARIMA modelling (rjd3x13::regarima())
and X-11 decomposition (rjd3x13::x11()).
A specification can be created with the functions
rjd3x13::regarima_spec(), rjd3x13::x11_spec() or
rjd3x13::x13_spec() and can be modified with the function:
-
for pre-processing:
rjd3toolkit::set_arima(),rjd3toolkit::set_automodel(),rjd3toolkit::set_basic(),rjd3toolkit::set_easter(),rjd3toolkit::set_estimate(),rjd3toolkit::set_outlier(),rjd3toolkit::set_tradingdays(),rjd3toolkit::set_transform(),rjd3toolkit::add_outlier(),rjd3toolkit::remove_outlier(),rjd3toolkit::add_ramp(),rjd3toolkit::remove_ramp(),rjd3toolkit::add_usrdefvar(); -
for decomposition:
rjd3x13::set_x11(); -
for benchmarking:
rjd3toolkit::set_benchmarking().
To get the current stable version (from the latest release):
# install.packages("remotes")
remotes::install_github("rjdemetra/rjd3x13@*release")To get the current development version from GitHub:
# install.packages("remotes")
remotes::install_github("rjdemetra/rjd3x13")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 2.13e-09 ***
#> TC (2000-06-01) 0.1590340 0.0288578 5.511 6.37e-08 ***
#> AO (2000-07-01) -0.2900774 0.0400551 -7.242 2.25e-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