SignalY (version 1.1.1)

filter_all: Apply Multiple Filters to a Series

Description

Convenience function that applies all three filtering methods (wavelet, EMD, HP-GC) to a time series and returns a consolidated comparison of results.

Usage

filter_all(
  y,
  wavelet_wf = "la8",
  wavelet_J = 4,
  wavelet_levels = c(3, 4),
  hpgc_prior = "weak",
  hpgc_chains = 4,
  hpgc_iterations = 20000,
  hpgc_burnin = 5000,
  verbose = FALSE
)

Value

A list of class "signaly_multifilter" containing results from all three methods and a comparison data frame.

Arguments

y

Numeric vector of the time series.

wavelet_wf

Wavelet filter for wavelet decomposition. Default "la8".

wavelet_J

Wavelet decomposition depth. Default 4.

wavelet_levels

Levels to combine for wavelet trend. Default c(3, 4).

hpgc_prior

Prior configuration for HP-GC. Default "weak".

hpgc_chains

Number of MCMC chains. Default 4.

hpgc_iterations

MCMC iterations. Default 20000.

hpgc_burnin

MCMC burn-in. Default 5000.

verbose

Logical for progress messages.

Examples

# \donttest{
y <- cumsum(rnorm(100)) + sin(seq(0, 4*pi, length.out = 100))
result <- filter_all(y, hpgc_iterations = 5000, hpgc_burnin = 1000)
# }