Constraining duty cycles through a Bayesian technique

The duty cycle (DC) of astrophysical sources is generally defined as the fraction of time 
during which the sources are active. It is used to both characterize their central engine 
and to plan further observing campaigns to study them. 
However, DCs, are generally not  provided with statistical uncertainties, since 
the standard approach is to perform Monte Carlo bootstrap simulations to evaluate them,
which can be quite time consuming for a large sample of sources. 
As an alternative, considerably less time-consuming approach, we
derived the theoretical expectation value for the DC and its error for sources whose state 
is one of two possible, mutually exclusive states, inactive (off) or flaring (on), 
as based on a finite set of independent observational data points. 
Following a Bayesian approach, we derived the analytical expression for the posterior,
the conjugated distribution adopted as prior, and the expectation value and variance. 
We applied our method to the specific case of the inactivity duty cycle 
(IDC) for supergiant fast X-ray transients, 
a subclass of flaring high mass X-ray binaries characterized by large dynamical ranges. 
We also studied IDC as a function of the number of observations in the sample. 
Finally, we compare the results with the theoretical expectations. 
We found excellent agreement with our findings based on the standard bootstrap method.  
Our Bayesian treatment can be applied to all sets of independent observations of 
two-state sources, such as active galactic nuclei, X-ray binaries, etc.  
In addition to being far less time consuming than bootstrap methods, 
the additional strength of this approach becomes obvious when considering a well-populated 
class of sources (Nsrc > 50) for which the prior can be fully characterized 
by fitting the distribution of the observed DCs for all sources in the class, so that,
through the prior, one can further constrain the DC of a new source
by exploiting the information acquired on the DC distribution derived from the other sources.