getSdBoot-SmoothedPG: Get bootstrap estimates for the standard deviation of the...
In quantspec: Quantile-Based Spectral Analysis of Time Series

Description Usage Arguments Details Value

Determines and returns an array of dimension [J,K1,K2], where J=length(frequencies), K1=length(levels.1), and K2=length(levels.2)). At position (j,k1,k2) the real part of the returned value is the standard deviation estimated from the real parts of the bootstrap replications and the imaginary part of the returned value is the standard deviation estimated from the imaginary part of the bootstrap replications. The estimate is determined from those bootstrap replicates of the estimator that have frequencies[j], levels.1[k1] and levels.2[k2] closest to the frequencies, levels.1 and levels.2 available in object; closest.pos is used to determine what closest to means.

## S4 method for signature 'SmoothedPG'
getSdBoot(
  object,
  frequencies = 2 * pi * (0:(lenTS(object@qPG@freqRep@Y) -
    1))/lenTS(object@qPG@freqRep@Y),
  levels.1 = getLevels(object, 1),
  levels.2 = getLevels(object, 2)
)

`object`	`SmoothedPG` of which to get the bootstrap estimates for the standard deviation.
`frequencies`	a vector of frequencies for which to get the result
`levels.1`	the first vector of levels for which to get the result
`levels.2`	the second vector of levels for which to get the result

Requires that the SmoothedPG is available at all Fourier frequencies from (0,pi]. If this is not the case the missing values are imputed by taking one that is available and has a frequency that is closest to the missing Fourier frequency; closest.pos is used to determine which one this is.

If there are no bootstrap replicates available (i. e., B == 0) an error is returned.

Note the “standard deviation” estimated here is not the square root of the complex-valued variance. It's real part is the square root of the variance of the real part of the estimator and the imaginary part is the square root of the imaginary part of the variance of the estimator.

Returns the estimate described above.

quantspec documentation built on July 15, 2020, 1:07 a.m.