BLOCK: A Bayesian block method to analyze structure in photon counting data
Abstract
Bayesian Blocks is a timedomain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The input is raw counting data, in any of three forms: timetagged photon events, binned counts, or timetospill data. The output is the most probable segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant, i.e. has no statistically significant variations. The idea is not that the source is deemed to have this discontinuous, piecewise constant form, rather that such an approximate and generic model is often useful. The analysis is based on Bayesian statistics.
This code is obsolete and yields approximate results; see Bayesian Blocks instead for an algorithm guaranteeing exact global optimization.
 Publication:

Astrophysics Source Code Library
 Pub Date:
 September 1999
 Bibcode:
 1999ascl.soft09005S
 Keywords:

 Software