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 LagEstimator
getSdBoot(
object,
frequencies = 2 * pi * (0:(length(object@lagOp@Y) - 1))/length(object@lagOp@Y),
levels.1 = getLevels(object, 1),
levels.2 = getLevels(object, 2)
)Returns the estimate described above.
LagEstimator of which to get the bootstrap
estimates for the standard deviation.
a vector of frequencies for which to get the result
the first vector of levels for which to get the result
the second vector of levels for which to get the result
Requires that the LagEstimator 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.