ci_wave_variance: Generate a Confidence intervval for a Univariate Time Series
In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description Usage Arguments Details Value Examples

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

1 2	ci_wave_variance(signal_modwt_bw, wv, type = "eta3", alpha_ov_2 = 0.025, robust = FALSE, eff = 0.6)

`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.

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

A matrix with the structure:

Column 1Wavelet Variance
Column 2Chi-squared Lower Bounds
Column 3Chi-squared Upper Bounds

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)