  In Cowell et al. (2007), a Bayesian network for analysis of mixed traces of
DNA was presented using gamma distributions for modelling peak sizes in the
electropherogram. It was demonstrated that the analysis was sensitive to the
choice of a variance factor and hence this should be adapted to any new trace
analysed. In the present paper we discuss how the variance parameter can be
estimated by maximum likelihood to achieve this. The unknown proportions of DNA
from each contributor can similarly be estimated by maximum likelihood jointly
with the variance parameter. Furthermore we discuss how to incorporate prior
knowledge about the parameters in a Bayesian analysis. The proposed estimation
methods are illustrated through a few examples of applications for calculating
evidential value in casework and for mixture deconvolution.
