rkhs_optimization_fun: Optimization Function of Reproducing Kernel Hilbert Space...

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

Optimization Function of Reproducing Kernel Hilbert Space (RKHS) Filters

Description

Export function used to compute the optimal bandwidth of Reproducing Kernel Hilbert Space (RKHS) filters

Usage

rkhs_optimization_fun(
  horizon = 6,
  leads = 0,
  degree = 2,
  kernel = c("Biweight", "Henderson", "Epanechnikov", "Triangular", "Uniform",
    "Triweight"),
  asymmetricCriterion = c("Timeliness", "FrequencyResponse", "Accuracy", "Smoothness"),
  density = c("uniform", "rw"),
  passband = 2 * pi/12
)

Arguments

horizon	horizon (bandwidth) of the symmetric filter.
leads	Leads of the filter (should be positive or 0).
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.

Examples

plot(rkhs_optimization_fun(horizon = 6, leads = 0,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X0 filter")
plot(rkhs_optimization_fun(horizon = 6, leads = 1,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X1 filter")
plot(rkhs_optimization_fun(horizon = 6, leads = 2,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X2 filter")
plot(rkhs_optimization_fun(horizon = 6, leads = 3,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X3 filter")
plot(rkhs_optimization_fun(horizon = 6, leads = 4,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X4 filter")
plot(rkhs_optimization_fun(horizon = 6, leads = 5,degree = 3, asymmetricCriterion = "Timeliness"),
     5.5, 6*3, ylab = "Timeliness",
     main = "6X5 filter")

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