sigex.getfrf: Computes frequency response function for desired signal and...

In jlivsey/sigex: Ecce Signum: Multivariate Signal Extraction

Computes frequency response function for desired signal and plots it

Description

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)

Usage

sigex.getfrf(data.ts, param, mdl, sigcomps, plotit = TRUE, grid)

Arguments

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
plotit	Boolean flag for whether frf should be plotted; only plots if N <= 3
grid	Desired number of frequencies for spectrum calculations

Details

Notes: take grid >> len, else numerical issues arise

Value

frf.comp: array of dimension c(N,N,grid), with complex number entries

jlivsey/sigex documentation built on March 20, 2024, 3:17 a.m.