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2015 Models with hidden regular variation: Generation and detection
Bikramjit Das, Sidney I. Resnick
Stoch. Syst. 5(2): 195-238 (2015). DOI: 10.1214/14-SSY141

Abstract

We review the notions of multivariate regular variation (MRV) and hidden regular variation (HRV) for distributions of random vectors and then discuss methods for generating models exhibiting both properties concentrating on the non-negative orthant in dimension two. Furthermore we suggest diagnostic techniques that detect these properties in multivariate data and indicate when models exhibiting both MRV and HRV are plausible fits for the data. We illustrate our techniques on simulated data, as well as two real Internet data sets.

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Bikramjit Das. Sidney I. Resnick. "Models with hidden regular variation: Generation and detection." Stoch. Syst. 5 (2) 195 - 238, 2015. https://doi.org/10.1214/14-SSY141

Information

Received: 1 March 2014; Published: 2015
First available in Project Euclid: 23 December 2015

zbMATH: 1346.60073
MathSciNet: MR3442427
Digital Object Identifier: 10.1214/14-SSY141

Subjects:
Primary: 28A33 , 60G17 , 60G51 , 60G70

Keywords: Conditional extreme value model , hidden regular variation , Multivariate heavy tails , regular variation , Tail estimation

Rights: Copyright © 2015 INFORMS Applied Probability Society

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Vol.5 • No. 2 • 2015
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