Tools for gamma-ray burst data mining

被引：1

作者：

Hakkila, J ^{[1
]}

Mallozzi, RS ^{[1
]}

Roiger, RJ ^{[1
]}

Haglin, DJ ^{[1
]}

Pendleton, GN ^{[1
]}

Meegan, CA ^{[1
]}

机构：

[1] Coll Charleston, Charleston, SC 29424 USA

来源：

GAMMA-RAY BURSTS IN THE AFTERGLOW ERA | 2001年

关键词：

D O I：

10.1007/10853853_15

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

Statistical evidence exists for two or more gamma-ray burst (GRB) subclasses, Pattern recognition algorithms also find this. However, not all statistical clusterings necessarily indicate separate source populations. Subclass identification can aid our understanding of systematic observational and instrumental biases. We demonstrate several computational pattern-finding tools, and show how these can be applied to the problems of GRB classification and subclass interpretation.

引用

页码：60 / 62

页数：3

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