filter_boosted_hp: Boosted HP filter

In kvasilopoulos/transx: Transform Univariate Time Series

Description

This function computes the cyclical component of the Boosted Hodrick-Prescot filter.

Usage

filter_boosted_hp(
  x,
  lambda = 1600,
  stopping = "nonstop",
  sig_p = 0.05,
  max_iter = 100
)

Arguments

x	[univariate vector] Univariate vector, numeric or ts object with only one dimension.
lambda	[numeric(1): 1600] Smoothness penalty parameter.
stopping:	[character: "nonstop"] If stopping = "adf" or "BIC", used stopping criteria. If stopping = "nonstop", iterated until max_iter
sig_p:	[numeric(1): 0.05] The significance level of the ADF test as the stopping criterion. It is used only when stopping == "adf".
max_iter:	[numeric(1): 100] The maximum number of iterations.

Value

Returns a vector with the same class and attributes as the input vector.

Source

This function has been retrieved and rewritten from https://github.com/zhentaoshi/Boosted_HP_filter/blob/master/R/BoostedHP.R

References

Phillips, P.C.B. and Shi, Z. (2021), BOOSTING: WHY YOU CAN USE THE HP FILTER. International Economic Review. https://doi.org/10.1111/iere.12495

Examples

unemp <- ggplot2::economics$unemploy
unemp_cycle <- filter_boosted_hp(unemp)
plotx(cbind(unemp, unemp_cycle))

kvasilopoulos/transx documentation built on Jan. 26, 2021, 6:14 p.m.