gmwm (version 2.0.0)

wvcov: Calculate the Asymptotic Covariance Matrix

Description

Places the Asymptotic Covariance Matrix in print form.

Usage

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

Arguments

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"

Value

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

Examples

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")