Bayesian model comparison using Gauss approximation on multicomponent mass spectra from CH4 plasma

We performed Bayesian model comparison on mass spectra from CH 4 rf process plasmas to detect radicals produced in the plasma. The key ingredient for its implementation is the highdimensional evidence integral. We apply Gauss approximation to evaluate the evidence. The results were compared with those calculated by the thermodynamic integration method using Markov Chain Monte Carlo technique. In spite of very large difference in the computation time between two methods a very good agreement was obtained. Alternatively, a Monte Carlo integration method based on the approximated Gaussian posterior density is presented. Its applicability to the problem of mass spectrometry is discussed.