Common arguments used in several functions in this package.
a \(T \times K\) array with T observations from the
\(K\)-dimensional time series \(\mathbf{X}_t\). Can be a matrix, data.frame,
or a multivariate ts object.
a \(T \times K\) array with T observations from the
\(K\)-dimensional whitened (whiten)
time series \(\mathbf{U}_t\). Can be a matrix, data.frame, or a
multivariate ts object.
an object of class "mvspectrum" representing
the multivariate spectrum of \(\mathbf{X}_t\) (not necessarily normalized).
multivariate spectrum of class 'mvspectrum' with
normalize = TRUE.
list; control settings for any iterative ForeCA
algorithm. See complete_algorithm_control for details.
list; control settings for entropy estimation.
See complete_entropy_control for details.
list; control settings for spectrum estimation.
See complete_spectrum_control for details.
string; method to estimate the entropy from discrete probabilities \(p_i\); here probabilities are the spectral density evaluated at the Fourier frequencies, \(\widehat{p}_i = \widehat{f}(\omega_i)\).
string; method for spectrum estimation; see method
argument in mvspectrum.
numeric; values of spectral density below threshold are set to
\(0\); default threshold = 0.
logarithm base; entropy is measured in ``nats'' for
base = exp(1); in ``bits'' if base = 2 (default).