serrsBayes-package | Bayesian modelling and quantification of Raman spectroscopy |
computeLogLikelihood | Compute the log-likelihood. |
copyLogProposals | Initialise the vector of Metropolis-Hastings proposals. |
effectiveSampleSize | Compute the effective sample size (ESS) of the particles. |
fitSpectraMCMC | Fit the model using Markov chain Monte Carlo. |
fitSpectraSMC | Fit the model using Sequential Monte Carlo (SMC). |
fitVoigtPeaksSMC | Fit the model with Voigt peaks using Sequential Monte Carlo (SMC). |
getBsplineBasis | Compute cubic B-spline basis functions for the given wavenumbers. |
getVoigtParam | Compute the pseudo-Voigt mixing ratio for each peak. |
marginalMetropolisUpdate | Update all of the parameters using a single Metropolis-Hastings step. |
mhUpdateVoigt | Update the parameters of the Voigt peaks using marginal Metropolis-Hastings. |
mixedVoigt | Compute the spectral signature using Voigt peaks. |
resampleParticles | Resample in place to avoid expensive copying of data structures, using a permutation of the ancestry vector. |
residualResampling | Compute an ancestry vector for residual resampling of the SMC particles. |
result | SMC particles for TAMRA+DNA (T20) |
reWeightParticles | Update the importance weights of each particle. |
serrsBayes | Bayesian modelling and quantification of Raman spectroscopy |
sumDlogNorm | Sum log-likelihoods of i.i.d. lognormal. |
sumDnorm | Sum log-likelihoods of Gaussian. |
weightedGaussian | Compute the spectral signature using Gaussian peaks. |
weightedLorentzian | Compute the spectral signature using Lorentzian peaks. |
weightedMean | Compute the weighted arithmetic means of the particles. |
weightedVariance | Compute the weighted variance of the particles. |