  We present a flavor and energy inference analysis for each high-energy
neutrino event observed by the IceCube observatory during six years of data
taking. Our goal is to obtain, for the first time, an estimate of the posterior
probability distribution for the most relevant properties, such as the neutrino
energy and flavor, of the neutrino-nucleon interactions producing shower and
track events in the IceCube detector. For each event the main observables in
the IceCube detector are the deposited energy and the event topology (showers
or tracks) produced by the Cherenkov light by the transit through a medium of
charged particles created in neutrino interactions. It is crucial to
reconstruct from these observables the properties of the neutrino which
generated such event. Here we describe how to achieve this goal using Bayesian
inference and Markov chain Monte Carlo methods.
