ci_wave_variance: Generate a Confidence intervval for a Univariate Time Series

In schoi355/gmwm: Generalized Method of Wavelet Moments

Generate a Confidence intervval for a Univariate Time Series

Description

Computes an estimate of the multiscale variance and a chi-squared confidence interval

Usage

ci_wave_variance(signal_modwt_bw, wv, type = "eta3",
  alpha_ov_2 = 0.025, robust = FALSE, eff = 0.6)

Arguments

signal_modwt_bw	A field<vec> that contains the brick walled modwt or dwt decomposition
wv	A vec that contains the wave variance.
type	A String indicating the confidence interval being calculated.
alpha_ov_2	A double that indicates the (1-p)*alpha confidence level.
robust	A boolean to determine the type of wave estimation.
eff	A double that indicates the efficiency.

Details

This function can be expanded to allow for other confidence interval calculations.

Value

A matrix with the structure:

• Column 1Wavelet Variance

• Column 2Chi-squared Lower Bounds

• Column 3Chi-squared Upper Bounds

Examples

set.seed(1337)
x = rnorm(100)
# Uses the internal MODWT function not associated with an S3 class.
decomp = modwt_cpp(x, filter_name = "haar", nlevels = 4, boundary = "periodic", brickwall = TRUE)
y = wave_variance(decomp)
ci_wave_variance(decomp, y, type = "eta3", alpha_ov_2 = 0.025)

schoi355/gmwm documentation built on April 11, 2022, 1:21 a.m.