| 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). |
| fitVoigtIBIS | Fit the model with Voigt peaks using iterated batch importance sampling (IBIS). |
| 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. |
| lsTamra | Surface-enhanced Raman spectram of tetramethylrhodamine+DNA (T20) |
| marginalMetropolisUpdate | Update all of the parameters using a single Metropolis-Hastings step. |
| methanol | Raman spectrum of methanol (CH3OH) |
| 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) |
| result2 | SMC particles for methanol (CH3OH) |
| reWeightParticles | Update the importance weights of each particle. |
| serrsBayes | Bayesian modelling and quantification of Raman spectroscopy |
| sumDexp | Sum log-likelihoods of i.i.d. exponential. |
| 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. |