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Trend-Cycle Estimation using the Cascade Linear Filter

Source: R/clf.R
clf_smoothing.Rd

Estimates the trend-cycle component using the Cascade Linear Filter (CLF) of length 13.

Usage

clf_smoothing(x, endpoints = c("cut-and-normalize", "ALF"), ...)

Arguments

x

An input time series (object of class "ts" or "mts").

endpoints

Character string specifying the method used for asymmetric filters. If "cut-and-normalize" (the default), the cut-and-normalize method is used (cut the symmetric filter and normalize the coefficients, as done by Statistics Canada); otherwise, Asymmetric Linear Filters (ALF) are used.

...

Other unused parameters.

Value

An object of class c("tc_estimates", "clf"). See tc_estimates() for a full description of the returned object.

References

Dagum, E. B., & Luati, A. (2008). A Cascade Linear Filter to Reduce Revisions and False Turning Points for Real Time Trend-Cycle Estimation. Econometric Reviews 28(1-3), 40–59. doi:10.1080/07474930802387837

Examples

if (FALSE) { # rjd3jars::check_java_version(silent = TRUE)
tc <- clf_smoothing(cars_registrations)
plot(tc, xlim = c(2022, 2025))
}