TRAMO model, pre-adjustment in TRAMO-SEATS

Usage

tramo(
  ts,
  spec = c("trfull", "tr0", "tr1", "tr2", "tr3", "tr4", "tr5"),
  context = NULL,
  userdefined = NULL
)

tramo_fast(
  ts,
  spec = c("trfull", "tr0", "tr1", "tr2", "tr3", "tr4", "tr5"),
  context = NULL,
  userdefined = NULL
)

Arguments

ts: a univariate time series.
spec: the model specification. Can be either the name of a predefined specification or a user-defined specification.
context: the dictionnary of variables.
userdefined: a vector containing the additional output variables (see tramoseats_dictionary()).

Value

the tramo() function returns a list with the results ("JD3_regarima_rslts" object), the estimation specification and the result specification, while tramo_fast() is a faster function that only returns the results.

Examples

library("rjd3toolkit")
#> 
#> Attaching package: ‘rjd3toolkit’
#> The following objects are masked from ‘package:stats’:
#> 
#>     aggregate, mad
y <- rjd3toolkit::ABS$X0.2.09.10.M
sp <- tramo_spec("trfull")
sp <- add_outlier(sp,
    type = c("AO"), c("2015-01-01", "2010-01-01")
)
tramo_fast(y, spec = sp)
#> Log-transformation: yes 
#> SARIMA model: (2,1,2) (0,1,1)
#> 
#> SARIMA coefficients:
#>    phi(1)    phi(2)  theta(1)  theta(2) btheta(1) 
#>  -0.09251   0.12325  -1.02295   0.24537  -0.43575 
#> 
#> Regression model:
#>          monday         tuesday       wednesday        thursday          friday 
#>      -1.131e-02       5.831e-03      -8.502e-05       1.293e-02      -2.076e-03 
#>        saturday              lp          easter AO (2010-01-01) AO (2015-01-01) 
#>       1.535e-02       3.881e-02       5.207e-02       3.674e-02      -9.888e-03 
#> AO (2000-06-01) AO (2000-07-01) 
#>       1.736e-01      -1.831e-01 
#> 
#> For a more detailed output, use the 'summary()' function.
sp <- set_transform(
    set_tradingdays(
        set_easter(sp, enabled = FALSE),
        option = "workingdays"
    ),
    fun = "None"
)
tramo_fast(y, spec = sp)
#> Log-transformation: no 
#> SARIMA model: (0,1,1) (0,1,1)
#> 
#> SARIMA coefficients:
#>  theta(1) btheta(1) 
#>   -0.8235   -0.2608 
#> 
#> Regression model:
#>          monday         tuesday       wednesday        thursday          friday 
#>        -11.7873          0.2507          3.0039         12.8309         -5.4519 
#>        saturday              lp AO (2010-01-01) AO (2015-01-01) AO (2000-06-01) 
#>         17.2998         33.6083         40.5331        -10.7096        192.7411 
#> AO (2000-07-01) AO (2005-04-01) 
#>       -200.7316       -177.1356 
#> 
#> For a more detailed output, use the 'summary()' function.
sp <- set_outlier(sp, outliers.type = c("AO"))
tramo_fast(y, spec = sp)
#> Log-transformation: no 
#> SARIMA model: (0,1,1) (0,1,1)
#> 
#> SARIMA coefficients:
#>  theta(1) btheta(1) 
#>   -0.8235   -0.2608 
#> 
#> Regression model:
#>          monday         tuesday       wednesday        thursday          friday 
#>        -11.7873          0.2507          3.0039         12.8309         -5.4519 
#>        saturday              lp AO (2010-01-01) AO (2015-01-01) AO (2000-06-01) 
#>         17.2998         33.6083         40.5331        -10.7096        192.7411 
#> AO (2000-07-01) AO (2005-04-01) 
#>       -200.7316       -177.1356 
#> 
#> For a more detailed output, use the 'summary()' function.