Data Analysis Through Segmentation: Bayesian Blocks and Beyond

Details Data Analysis Through Segmentation: Bayesian Blocks and Beyond Data Analysis Through Segmentation: Bayesian Blocks and Beyond

Aug 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004head....8.3101s&link_type=abstract

American Astronomical Society, HEAD meeting #8, #31.01; Bulletin of the American Astronomical Society, Vol. 36, p.1200

Statistics

Methodology

Scientific paper

This tutorial covers analysis methods for detecting and characterizing structure in time series data, based on optimal segmentation of the observational interval. Examples include cases where the fitness function to be optimized is the Bayesian posterior for the full piece-wise constant model of the data, yielding the Bayesian Blocks representation. For any fitness function a novel dynamic programming algorithm finds the global optimum partition, over all possible partitions of the interval (an exponentially large search space!) in time proportional to the square of the number of data points.
This methodology has been extended to 2D data (e.g. images or photon maps), 3D data (e.g. from redshift surveys), and data of higher dimension. These problems can be solved by transformation first into finite combinatorial optimizations, and then into equivalent one dimensional problems that can be solved with the 1D algorithm discussed above.
The tutorial itself, plus descriptions of MatLab implementations of the algorithms and sample applications, will be made available electronically. I gratefully acknowledge support from the NASA Applied Information System Research Program, the Intelligent Systems Program, and the NASA Ames Director's Discretionary Fund.

Affiliated with

Also associated with

No associations

Rating

Data Analysis Through Segmentation: Bayesian Blocks and Beyond does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Data Analysis Through Segmentation: Bayesian Blocks and Beyond, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Data Analysis Through Segmentation: Bayesian Blocks and Beyond will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1178695