summary.mWaveD: Summary Output for the mWaveD object

In jrwishart/mwaved: Multichannel Wavelet Deconvolution with Additive Long Memory Noise

Description

Gives some numerical summaries of a mWaveD object.

Usage

## S3 method for class 'mWaveD'
summary(object, ...)

Arguments

object	A mWaveD object which is a list containing all the information for a multichannel deconvolution analysis produced by the multiWaveD function.
...	Arguments to be passed to methods.

Value

Text output giving summary information of the input and output analysis including,

• Degree of Meyer wavelet used in the analysis.

• Number of observations, within each channel and number of channels present.

• Resolution levels used (j0 to j1)

• Blur type assumed in the analysis (direct, smooth or box.car)

• Matrix summarising the noise levels in each channel (and Fourier decay information for the smooth case)

• Summaries of the severity of the thresholding applied amongst the resolutions.

See Also

multiWaveD

Examples

library(mwaved)
# Simulate the multichannel doppler signal.
m <- 3
n <- 2^10
t <- (1:n)/n
signal <- makeDoppler(n)
# Create multichannel version with smooth blur
shape <- seq(from = 0.5, to = 1, length = m)
scale <- rep(0.25, m)
G <- gammaBlur(n, shape, scale)
X <- blurSignal(signal, G)
# Add noise with custom signal to noise ratio
SNR <- c(10,15,20)
E <- multiNoise(n, sigma = sigmaSNR(X, SNR), alpha = c(0.5, 0.75, 1))
# Create noisy & blurred multichannel signal
Y <- X + E
mWaveDObject <- multiWaveD(Y, G)
summary(mWaveDObject)

jrwishart/mwaved documentation built on Oct. 31, 2021, 6:16 p.m.