tramo_outliers: Outlier Detection with a Tramo Model

In palatej/rjd3tramoseats: Seasonal Adjustment with TRAMO-SEATS in 'JDemetra+ 3.x'

Outlier Detection with a Tramo Model

Description

Tramo is a particular regarima model estimation algorithm, mainly used to linearized the series before performing a decomposition with Seats

Usage

tramo_outliers(
  y,
  order = c(0L, 1L, 1L),
  seasonal = c(0L, 1L, 1L),
  mean = FALSE,
  X = NULL,
  X.td = NULL,
  ao = TRUE,
  ls = TRUE,
  tc = FALSE,
  so = FALSE,
  cv = 0,
  ml = FALSE,
  clean = FALSE
)

Arguments

y	the dependent variable (a ts object).
order, seasonal	the orders of the ARIMA model.
mean	Boolean to include or not the mean.
X	user defined regressors (other than calendar).
X.td	calendar regressors.
ao, ls, so, tc	Boolean to indicate which type of outliers should be detected.
cv	numeric. The entered critical value for the outliers' detection procedure. If equal to 0 the critical value for the outliers' detection procedure is automatically determined by the number of observations.
ml	Use of maximum likelihood (otherwise approximation by means of Hannan-Rissanen).
clean	Clean missing values at the beginning/end of the series. Regression variables are automatically resized, if need be.

Value

a "JD3_REGARIMA_OUTLIERS" object.

Examples

tramo_outliers(rjd3toolkit::ABS$X0.2.09.10.M)

palatej/rjd3tramoseats documentation built on April 17, 2025, 11:29 p.m.