Posterior distribution for pseudo-Voigt parameters, obtained by running `fitVoigtPeaksSMC` on a spectrum from Gracie et al. (Anal. Chem., 2016). 1000 SMC particles with 32 peaks. For details, see the vignette.
resultA list containing 15 variables:
normalised importance weights for each particle
location parameters of 32 peaks
amplitudes of 32 peaks
scale of the Gaussian (RBF) broadening
scale of the Lorentzian (Cauchy) broadening
standard deviation of the additive white noise
smoothing parameter of the cubic B-splines
List of informative priors
history of the effective sample size
history of the likelihood tempering
history of Metropolis-Hastings acceptance rates
history of Metropolis-Hastings steps
history of times for each SMC iteration
computation time taken by the SMC algorithm