Bayesian analysis of data for a stochastic detector

A study of the inverse problem, related to individual electron detectors for track nanodosimetry is presented. It is shown that, despite the stochastic character of these detectors, events such as the presence of clusters can be inferred from data independently of the conditions of measurement. An algorithmic reconstruction of the a priori probability distribution of ionisation is proposed. (author)