localpolynomials: Apply Local Polynomials Filters

In palatej/rjdfilters: Trend-Cycle Extraction with Linear Filters

Apply Local Polynomials Filters

Description

Apply Local Polynomials Filters

Usage

localpolynomials(
  x,
  horizon = 6,
  degree = 3,
  kernel = c("Henderson", "Uniform", "Biweight", "Trapezoidal", "Triweight", "Tricube",
    "Gaussian", "Triangular", "Parabolic"),
  endpoints = c("LC", "QL", "CQ", "CC", "DAF"),
  ic = 4.5,
  tweight = 0,
  passband = pi/12
)

Arguments

x	input time-series.
horizon	horizon (bandwidth) of the symmetric filter.
degree	degree of polynomial.
kernel	kernel uses.
endpoints	methode for endpoints.
ic	ic ratio.
tweight	timeliness weight.
passband	passband threshold.

Value

the target signal

References

Proietti, Tommaso and Alessandra Luati (2008). “Real time estimation in local polynomial regression, with application to trend-cycle analysis”.

See Also

lp_filter

Examples

x <- retailsa$AllOtherGenMerchandiseStores
trend <- localpolynomials(x, horizon = 6)
plot(x)
lines(trend, col = "red")

palatej/rjdfilters documentation built on May 8, 2023, 6:28 a.m.