set_outlier: Set Outlier Specification

In palatej/rjd3modelling: Time Series Modelling Functions with 'JDemetra+ 3.0'

Set Outlier Specification

Description

Set Outlier Specification

Usage

set_outlier(
  x,
  span.type = c(NA, "All", "From", "To", "Between", "Last", "First", "Excluding"),
  d0 = NULL,
  d1 = NULL,
  n0 = 0,
  n1 = 0,
  outliers.type = NA,
  critical.value = NA,
  tc.rate = NA,
  method = c(NA, "AddOne", "AddAll"),
  maxiter = NA,
  lsrun = NA,
  eml.est = NA
)

Arguments

x	the specification.
span.type, d0, d1, n0, n1	parameters to specifiy the span of to be used. d0 and d1 characters in the format "YYYY-MM-DD" to specify first/last date of the span when type equals to "From", "To" or "Between". n0 and n1 numerics to specify the number of periods at the beginning/end of the series to be used for the span (type equals to "From", "To") or to exclude (type equals to "Excluding").
outliers.type	vector of characters of the outliers to be automatically detected. "AO" for additive outliers, "TC" for transitory changes "LS" for level shifts and "SO" for seasonal outliers. For example outliers.type = c("AO", "LS") to enable the detection of additive outliers and level shifts. If outliers.type = NULL or outliers.type = character(), automatic detection of outliers is disabled.
critical.value	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 in the outlier detection time span.
tc.rate	the rate of decay for the transitory change outlier.
method	(REGARIMA/X13 Specific) determines how the program successively adds detected outliers to the model. At present, only the "AddOne" method is supported.
maxiter	(REGARIMA/X13 Specific) TODO
lsrun	(REGARIMA/X13 Specific) TODO
eml.est	(TRAMO Specific) logical for the exact likelihood estimation method. It controls the method applied for a parameter estimation in the intermediate steps of the automatic detection and correction of outliers. If TRUE, an exact likelihood estimation method is used. When FALSE, the fast Hannan-Rissanen method is used.

palatej/rjd3modelling documentation built on Jan. 3, 2023, 10:19 p.m.