sigex.conditions: Computes condition number for a covariance matrix

In jlivsey/sigex: Ecce Signum: Multivariate Signal Extraction

Computes condition number for a covariance matrix

Description

Background: a non-negative definite matrix Sigma has a Generalized Cholesky Decomposition (GCD) of the form Sigma = L where L is unit lower triangular and D is diagonal with non-negative entries, referred to as the Schur complements of Sigma. The number of nonzero Schur complements equals the rank of Sigma. The condition numbers can be computed by dividing D by the diagonal of Sigma. 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.conditions(data.ts, psi, mdl)

Arguments

data.ts	A T x N matrix ts object (with no missing values) corresponding to N time series of length T
psi	A vector of all the real hyper-parameters
mdl	The specified sigex model, a list object

Value

conds: a S x N matrix of condition numbers, where S is the number of components. Each row gives the N condition numbers for the innovation covariance matrix of the corresponding latent component.

jlivsey/sigex documentation built on May 25, 2024, 4:17 a.m.