Access model specification, SA and pre-adjustment in X13 and TRAMO-SEATS
Below functions access different parts of the final model specification as included in the "SA", "regarima", "SA_spec" and "regarima_spec" S3 class objects.
s_estimate(object = NA) s_transform(object = NA) s_usrdef(object = NA) s_preOut(object = NA) s_preVar(object = NA) s_td(object = NA) s_easter(object = NA) s_out(object = NA) s_arima(object = NA) s_arimaCoef(object = NA) s_fcst(object = NA) s_span(object = NA) s_x11(object = NA) s_seats(object = NA)
object |
object of one of the classes: |
s_estimate returns a data.frame with the estimate variables
s_transform returns a data.frame with the transform varaibles
s_usrdef returns a data.frame with the user-defined regressors (outliers and variables) model specification, indicating if those variables are included in the model and if coefficients are pre-specified
s_preOut returns a data.frame with the pre-specified outliers
s_preVar returns a list with the information on the user-defined variables, including: series - the time series and description - data.frame with the variable type and coefficients
s_td returns a data.frame with the trading.days variables
s_easter returns a data.frame with the easter variables
s_out returns a data.frame with the outliers detection variables
s_arima returns a data.frame with the arima variables
s_arimaCoef returns a data.frame with the user-specified ARMA coefficients
s_fcst returns a data.frame with the forecast horizon
s_span returns a data.frame with the span variables
s_x11 returns a data.frame with the x11 variables
s_seats returns a data.frame with the seats variables
Info on 'JDemetra+', usage and functions: https://ec.europa.eu/eurostat/cros/content/documentation_en
myseries <- ipi_c_eu[, "FR"]
myreg1 <- regarima_x13(myseries, spec = "RG5c")
myspec1 <- regarima_spec_x13(myreg1,
estimate.from = "2005-10-01",
outlier.from = "2010-03-01")
s_estimate(myreg1)
s_estimate(myspec1)
s_transform(myreg1)
s_transform(myspec1)
s_usrdef(myreg1)
s_usrdef(myspec1)
myspec2 <- regarima_spec_x13(myreg1, usrdef.outliersEnabled = TRUE,
usrdef.outliersType = c("LS", "AO"),
usrdef.outliersDate = c("2009-10-01", "2005-02-01"))
myreg2 <- regarima(myseries, myspec2)
s_preOut(myreg2)
s_preOut(myspec2)
var1 <- ts(rnorm(length(myseries))*10, start = start(myseries), frequency = 12)
var2 <- ts(rnorm(length(myseries))*100, start = start(myseries), frequency = 12)
var3 <- ts.union(var1, var2)
myspec3 <- regarima_spec_x13(spec = "RG5c",
usrdef.varEnabled = TRUE,
usrdef.var = var3)
myreg3 <- regarima(myseries, myspec3)
s_preVar(myspec3)
s_preVar(myreg3)
s_td(myreg1)
s_td(myspec1)
s_easter(myreg1)
s_easter(myspec1)
s_out(myreg1)
s_out(myspec1)
s_arima(myreg1)
s_arima(myspec1)
myspec4 <- regarima_spec_x13(myreg1, automdl.enabled = FALSE,
arima.coefEnabled = TRUE,
arima.p = 1,arima.q = 1, arima.bp = 1, arima.bq = 1,
arima.coef = rep(0.2, 4),
arima.coefType = rep("Initial", 4))
myreg4 <- regarima(myseries, myspec4)
s_arimaCoef(myreg4)
s_arimaCoef(myspec4)
s_fcst(myreg1)
s_fcst(myspec1)
s_span(myreg1)
s_span(myspec1)
myspec5 <- x13_spec(spec = "RSA5c", x11.seasonalComp = FALSE)
mysa5 <- x13(myseries, myspec5)
s_x11(mysa5)
s_x11(myspec5)
myspec6 <- tramoseats_spec(spec = "RSAfull", seats.approx = "Noisy")
mysa6 <- tramoseats(myseries, myspec6)
s_seats(mysa6)
s_seats(mysa6)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.