wvcov: Calculate the Asymptotic Covariance Matrix
In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description Usage Arguments Value Author(s) Examples

Places the Asymptotic Covariance Matrix in print form.

1	wvcov(signal.modwt, signal.wvar, compute.v = "diag")

`signal.modwt`	A `modwt` object that contains the modwt decomposition.
`signal.wvar`	A `wvar` object that contains the wavelet variance.
`compute.v`	A `string` that indicates the type of covariance matrix to compute. Supports: "diag"

A list with the structure:

"V": Covariance Matrix
"V.r": Covariance Matrix
"nlevels": Level of decomposition J
"compute.v": Type of Covariance Matrix
"robust": Robust active
"eff": Efficiency level for Robust
"scales": Tau scales (2^(1:J))
"wv.empir": Empirical Wavelet Variance

JJB

set.seed(999)
x = rnorm(100)
decomp = modwt(x)
wv = wvar(x)
out = wvcov(decomp, wv, compute.v="diag")

# Robust
decomp = modwt(x)
wv = wvar(x, robust = TRUE)
out = wvcov(decomp, wv, compute.v="diag")