rkhs_filter: Reproducing Kernel Hilbert Space (RKHS) Filters

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

Reproducing Kernel Hilbert Space (RKHS) Filters

Description

Estimation of a filter using Reproducing Kernel Hilbert Space (RKHS)

Usage

rkhs_filter(
  horizon = 6,
  degree = 2,
  kernel = c("Biweight", "Henderson", "Epanechnikov", "Triangular", "Uniform",
    "Triweight"),
  asymmetricCriterion = c("Timeliness", "FrequencyResponse", "Accuracy", "Smoothness",
    "Undefined"),
  density = c("uniform", "rw"),
  passband = 2 * pi/12,
  optimalbw = TRUE,
  optimal.minBandwidth = horizon,
  optimal.maxBandwidth = 3 * horizon,
  bandwidth = horizon + 1
)

Arguments

horizon	horizon (bandwidth) of the symmetric filter.
degree	degree of polynomial.
kernel	kernel uses.
asymmetricCriterion	the criteria used to compute the optimal bandwidth. If "Undefined", m+1 is used.
density	hypothesis on the spectral density: "uniform" (= white woise, the default) or "rw" (= random walk).
passband	passband threshold.
optimalbw	boolean indicating if the bandwith should be choosen by optimisation (between optimal.minBandwidth and optimal.minBandwidth using the criteria asymmetricCriterion). If optimalbw = FALSE then the bandwith specified in bandwidth will be used.
optimal.minBandwidth, optimal.maxBandwidth	the range used for the optimal bandwith selection.
bandwidth	the bandwidth to use if optimalbw = FALSE.

Value

An object of class "rkhs_filter", which is a list of 4 elements:

• "internal"Java object used for internal functions

• "filters.coef"The coefficients of the selected filter

• "filters.gain"The gain function between 0 and pi (601 observations)

• "filters.phase"The phase function between 0 and pi (601 observations)

References

Dagum, Estela Bee and Silvia Bianconcini (2008). “The Henderson Smoother in Reproducing Kernel Hilbert Space”. In: Journal of Business & Economic Statistics 26, pp. 536–545. URL: https://ideas.repec.org/a/bes/jnlbes/v26y2008p536-545.html.

Examples

rkhs <- rkhs_filter(horizon = 6, asymmetricCriterion = "Timeliness")
plot_coef(rkhs)

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