sigex.frf | R Documentation |
Background: A sigex model consists of process x = sum y, for stochastic components y. Each component process y_t is either stationary or is reduced to stationarity by application of a differencing polynomial delta(B), i.e. w_t = delta(B) y_t is stationary. We have a model for each w_t process, and can compute its autocovariance function (acf), and denote its autocovariance generating function (acgf) via gamma_w (B). The signal extraction filter for y_t is determined from this acgf and delta. param is the name for the model parameters entered into a list object with a more intuitive structure, whereas psi refers to a vector of real numbers containing all hyper-parameters (i.e., reals mapped bijectively to the parameter manifold)
sigex.frf(data.ts, param, mdl, sigcomps, grid)
data.ts |
A T x N matrix ts object |
param |
The model parameters entered into a list object |
mdl |
The specified sigex model, a list object |
sigcomps |
Indices of the latent components composing the signal |
grid |
Desired number of frequencies for spectrum calculations |
Notes: take grid >> len, else numerical issues arise
frf.wk: array of dimension c(N,N,grid), with complex number entries
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