Smoothing using the Henderson filter

Usage

henderson_smoothing(
  x,
  endpoints = c("Musgrave", "QL", "CQ", "CC", "DAF", "CN"),
  length = NULL,
  icr = NULL,
  local_icr = FALSE,
  asymmetric_var = FALSE,
  degree = 3,
  ...
)

Arguments

x: input time-series.
endpoints: Method used for the asymmetric filter. By default the Musgrave method is used
length: the length of the
icr: I/C ratio used for the asymmetric filter.
local_icr: if TRUE, the I/C ratio is estimated locally (as described in Quartier-la-Tente, A. (2024)) instead of globally.
asymmetric_var: when local_icr = TRUE, if asymmetric_var = TRUE then the variance is estimated for each asymmetric filters instead of using the variance associated to the symmetric estimates.
degree: if local_icr = TRUE, degree of polynomial used to estimate the local bias parameter.
...: other parameters passed to rjd3filters::lp_filter().

References

Quartier-la-Tente, A. (2024). Improving Real-Time Trend Estimates Using Local Parametrization of Polynomial Regression Filters. Journal of Official Statistics, 40(4), 685-715. https://doi.org/10.1177/0282423X241283207.