Jd. Scargle, Studies in astronomical time series analysis. V. Bayesian blocks, a new method to analyze structure in photon counting data, ASTROPHYS J, 504(1), 1998, pp. 405-418
I describe a new time-domain algorithm for detecting localized structures (
bursts), revealing pulse shapes, and generally characterizing intensity var
iations. The input is raw counting data, in any of three forms: time-tagged
photon events (TTE), binned counts, or time-to-spill (TTS) data. The outpu
t 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 de
emed to have this discontinuous, piecewise constant form, rather that such
an approximate and generic model is often useful. Since the analysis is bas
ed on Bayesian statistics, I call the resulting structures Bayesian blocks.
Unlike most, this method does not stipulate time bins-instead the data det
ermine a piecewise constant representation. Therefore the analysis procedur
e itself does not impose a lower limit to the timescale on which variabilit
y can be detected. Locations, amplitudes, and rise and decay times of pulse
s within a time series can be estimated independent of any pulse-shape mode
l-but only if they do not overlap too much, as deconvolution is not incorpo
rated. The Bayesian blocks method is demonstrated by analyzing pulse struct
ure in BATSE gamma-ray data.(2).