Man pages for serrsBayes
Bayesian Modelling of Raman Spectroscopy

computeLogLikelihoodCompute the log-likelihood.
copyLogProposalsInitialise the vector of Metropolis-Hastings proposals.
effectiveSampleSizeCompute the effective sample size (ESS) of the particles.
fitSpectraMCMCFit the model using Markov chain Monte Carlo.
fitSpectraSMCFit the model using Sequential Monte Carlo (SMC).
fitVoigtPeaksSMCFit the model with Voigt peaks using Sequential Monte Carlo...
getBsplineBasisCompute cubic B-spline basis functions for the given...
getVoigtParamCompute the pseudo-Voigt mixing ratio for each peak.
marginalMetropolisUpdateUpdate all of the parameters using a single...
mhUpdateVoigtUpdate the parameters of the Voigt peaks using marginal...
mixedVoigtCompute the spectral signature using Voigt peaks.
resampleParticlesResample in place to avoid expensive copying of data...
residualResamplingCompute an ancestry vector for residual resampling of the SMC...
resultSMC particles for TAMRA+DNA (T20)
reWeightParticlesUpdate the importance weights of each particle.
serrsBayesBayesian modelling and quantification of Raman spectroscopy
sumDlogNormSum log-likelihoods of i.i.d. lognormal.
sumDnormSum log-likelihoods of Gaussian.
weightedGaussianCompute the spectral signature using Gaussian peaks.
weightedLorentzianCompute the spectral signature using Lorentzian peaks.
weightedMeanCompute the weighted arithmetic means of the particles.
weightedVarianceCompute the weighted variance of the particles.
serrsBayes documentation built on June 5, 2018, 5:04 p.m.