| result {serrsBayes} | R Documentation |
SMC particles for TAMRA+DNA (T20)
Description
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.
Usage
result
Format
A list containing 15 variables:
- weights
normalised importance weights for each particle
- location
location parameters of 32 peaks
- beta
amplitudes of 32 peaks
- scale_G
scale of the Gaussian (RBF) broadening
- scale_L
scale of the Lorentzian (Cauchy) broadening
- sigma
standard deviation of the additive white noise
- lambda
smoothing parameter of the cubic B-splines
- priors
List of informative priors
- ess
history of the effective sample size
- kappa
history of the likelihood tempering
- accept
history of Metropolis-Hastings acceptance rates
- mhSteps
history of Metropolis-Hastings steps
- times
history of times for each SMC iteration
- time
computation time taken by the SMC algorithm