Package index • serrsBayes

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).
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.
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 serrsBayes-package: 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.