computeLogLikelihood: Compute the log-likelihood.

In serrsBayes: Bayesian Modelling of Raman Spectroscopy

Description

This is an internal function that is only exposed on the public API for unit testing purposes. It computes the log-likelihood of the spline and the noise, once the spectral signature has been subtracted from the observed data. Thus, it can be used with either Lorentzian, Gaussian, or pseudo-Voigt broadening functions.

Usage

computeLogLikelihood(
  obsi,
  lambda,
  prErrNu,
  prErrSS,
  basisMx,
  eigVal,
  precMx,
  xTx,
  aMx,
  ruMx
)

Arguments

obsi	Vector of residuals after the spectral signature has been subtracted.
lambda	smoothing parameter of the penalised B-spline.
prErrNu	hyperparameter of the additive noise
prErrSS	hyperparameter of the additive noise
basisMx	Matrix of B-spline basis functions
eigVal	eigenvalues of the Demmler-Reinsch factorisation
precMx	precision matrix for the spline
xTx	sparse matrix cross-product
aMx	orthoganal matrix A from the Demmler-Reinsch factorisation
ruMx	product of Ru from the Demmler-Reinsch factorisation

Value

The logarithm of the likelihood.

serrsBayes documentation built on June 28, 2021, 5:14 p.m.