Analytical peak fitting for gamma-ray spectrum analysis with Ge detectors

A class of fitting functions which provides an adequate representation of a wide variety of Ge detector spectral peaks is proposed. Members of this class are composed of a summation of five functions, containing a total of ten parameters. A new fitting technique, based on Bayesian statistics, is also proposed. By adding a penalty function to the normal chi-square term, this technique improves the speed of convergence and the reliability of the minimization algorithms used during peak fitting. The Bayesian approach offers a satisfactory statistical treatment of peak-area uncertainties, avoiding the often unreliable approximations inherent in most other approaches to uncertainty estimation. (orig.)