Compute DPCA filter coefficients
Estimate regresson operators in a lagged linear model
Eigendevompose a frequency domain operator at each frequency
Compute operator norms of elements of a filter
Inverse Fourier transform for operators
Compute scores of dynamic principal components
Retrieve a process from given scores
Generate a linear process from
Estimate the optimal dimension in linear regression problem
Convolution of a process X with an operator A.
Estimate the optimal dimension in linear regression problem
Compute a ratio of two spectral densities
Test significance of coefficients in linear model estimator
Frequency-wise or component-wise Kronecker product.
Compute fourier transform of given series of operators
Generate brownian bridges
Compute the cross spectral density of processes X and Y
Compute a spectral norm of given matrix P
Moving avarege process
Plot a frequency domain operator
Truncates a time domain object to specified lags
Compute a mean square error between X and Y
Compute cross covariance with a given lag
Determine the subspace dimension for inversion in speclagreg Transpose pointwise timedom or freqdom object
Frequency-wise or component-wise matrix product.
Create a frequency domain operator
Check if a given object is a frequency domain matrix
Simulate a multivariate autoregressive time series
Compute a kronecker product of two spectral densities
Estimate the optimal dimension in linear regression problem
Generate a linear process from
Estimate the covariance structure within a given window \(k \in [-q,q]\)
Compute a product of two spectral densities
Creates a time domain operator
Invert first K eigendirections of the matrix.
Compute an inverse of a given Frequency Domain Operator
Check if a given object is a time domain object
Generate brownian motions