BLOCK: Bayesian block method to analyze structure in photon

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owlice
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BLOCK: A Bayesian block method to analyze structure in photon counting data

Post by owlice » Thu Aug 16, 2012 1:09 pm

[c]BLOCK: A Bayesian block method to analyze structure in photon counting data[/c][/b]
Abstract: Bayesian Blocks is a time-domain 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: time-tagged photon events, binned counts, or time-to-spill 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This code is obsolete and yields approximate results; see Bayesian Blocks instead for an algorithm guaranteeing exact global optimization.

Credit: Scargle, Jeffrey D.

Site: http://dx.doi.org/10.20356/C4CC72
http://adsabs.harvard.edu/abs/1998ApJ...504..405S

Bibcode: 1999ascl.soft09005S

ID: ascl:9909.005
Last edited by Ada Coda on Tue Jun 19, 2018 6:29 pm, edited 1 time in total.
Reason: Updated code entry.
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