summary.mvLSW: Print a Summary of mvLSW Object

In mvLSW: Multivariate, Locally Stationary Wavelet Process Estimation

Print a Summary of mvLSW Object

Description

Prints a summary of the information contained within a mvLSW classed object.

Usage

  ## S3 method for class 'mvLSW'
summary(object, ...)
  ## S3 method for class 'mvLSW'
print(x, ...)

Arguments

object, x	A mvLSW object.
...	Additional arguments.

Details

The command prints to screen a summary of the information contained within a mvLSW object. Information printed includes: dimensions, wavelet function, the smoothing regime applied, smoothing kernel(s), generalized cross-validation gamma deviance criteria score, application of the bias correction and minimum eigenvalue from across all spectral matrices.

Value

This command returns nothing, only prints a summary to the console.

References

Taylor, S.A.C., Park, T.A. and Eckley, I. (2019) Multivariate locally stationary wavelet analysis with the mvLSW R package. Journal of statistical software 90(11) pp. 1–16, doi: 10.18637/jss.v090.i11.

See Also

mvEWS, as.mvLSW.

Examples

## Generate a bivariate time series
set.seed(100)
X <- matrix(rnorm(2 * 2^8), ncol = 2)
X[1:2^7, 2] <- 3 * (X[1:2^7, 2] + 0.95 * X[1:2^7, 1])
X[-(1:2^7), 2] <- X[-(1:2^7), 2] - 0.95 * X[-(1:2^7), 1]
X[-(1:2^7), 1] <- X[-(1:2^7), 1] * 4
X <- as.ts(X)

## Haar wavelet, apply same smoothing to all levels & optimize
EWS <- mvEWS(X, kernel.name = "daniell", kernel.param = 20,
  optimize = TRUE)
summary(EWS)
print(EWS)
plot(EWS, style = 2, info = 1)

mvLSW documentation built on June 14, 2022, 5:06 p.m.