Campus Units
Statistics
Document Type
Article
Publication Version
Published Version
Publication Date
8-2017
Journal or Book Title
Monthly Notices of the Royal Astronomical Society
Volume
469
Issue
3
First Page
3374
Last Page
3389
DOI
10.1093/mnras/stx1024
Abstract
Clustering methods are an important tool to enumerate and describe the different coherent kind of gamma-ray bursts (GRBs). But their performance can be affected by a number of factors such as the choice of clustering algorithm and inherent associated assumptions, the inclusion of variables in clustering, nature of initialization methods used or the iterative algorithm or the criterion used to judge the optimal number of groups supported by the data. We analysed GRBs from the Burst and Transient Source Experiment (BATSE) 4Br Catalog using k-means and Gaussian-mixture-models-based clustering methods and found that after accounting for all the above factors, all six variables – different subsets of which have been used in the literature – that are, namely, the flux duration variables (T50, T90), the peak flux (P256) measured in 256 ms bins, the total fluence (Ft) and the spectral hardness ratios (H32 and H321) contain information on clustering. Further, our analysis found evidence of five different kinds of GRBs and that these groups have different kinds of dispersions in terms of shape, size and orientation. In terms of duration, fluence and spectrum, the five types of GRBs were characterized as intermediate/faint/intermediate, long/intermediate/soft, intermediate/intermediate/intermediate, short/faint/hard and long/bright/intermediate.
Copyright Owner
The Authors
Copyright Date
2017
Language
en
File Format
application/pdf
Recommended Citation
Chattopadhyay, Souradeep and Maitra, Ranjan, "Gaussian-mixture-model-based cluster analysis finds five kinds of gamma-ray bursts in the BATSE catalogue" (2017). Statistics Publications. 164.
https://lib.dr.iastate.edu/stat_las_pubs/164
Included in
Categorical Data Analysis Commons, Other Astrophysics and Astronomy Commons, Statistical Methodology Commons
Comments
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.