We present a model independent analysis method following Bayesian statistics to analyse data from any counting experiment and apply it to the search for neutrinos from point sources. The Bayesian approach allows us to obtain the full probability distribution function for both the background and the signal rate. As such, we have direct access to the upper limits. The upper limit derivation directly compares with the frequentist method developed by Feldman and Cousins and is robust in the case of low-counting observations. Furthermore, it allows also to account for previous upper limits of other analysis via the concept of prior information.
To investigate the validity of our Bayesian approach, we have applied this method to the public IceCube 40-string configuration data for 10 nearby blazars and we have obtained a flux upper limit, which is in agreement with the upper limit determined with the frequentist method mentioned. Furthermore, the upper limit obtained compares very well with the previously published result of IceCube, using the same data set.
