All functions

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.

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.

reWeightParticles()

Update the importance weights of each particle.

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)

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.