NoiseNormalsSolution
The inverse of the normal matrix of inputfileNormalEquation represents the covariance matrix of the estimated parameters. This program generates a noise vector with \[ \M\Sigma(\M e) = \M N^{-1}, \]if generated input noise is standard white noise.
The noise vector is computed with \[ \M e = \M W^{-T} \M z, \]where $\M z$ is the generated noise and $\M W$ is the cholesky upper triangle matrix of the normal matrix $\M N=\M W^T\M W$.
| Name | Type | Annotation |
|---|---|---|
outputfileNoise | filename | generated noise as matrix: parameterCount x sampleCount |
inputfileNormalEquation | filename | |
noise | noiseGenerator | |
sampleCount | uint | number of samples to be generated |
useEigenvalueDecomposition | boolean | use eigenvalue decomposition |