Statistical Inference for Heavy-Tailed Distributions in Technical Systems

Author

Karagrigoriou, Alex ; Vonta, Ilia

Author_Institution

Dept. of Math., Univ. of the Aegean, Samos, Greece

fYear

2014

fDate

8-12 Sept. 2014

Firstpage

412

Lastpage

419

Abstract

In this work we explore the class of heavy-tailed distributions and discuss their signicance in reliability engineering. At the same time we discuss measures of divergence which are extensively used in statistics in various elds. In this paper we rely on such measures to evaluate the residual and past lifetimes of events which are associated with the tail part of the distribution. More specifically, we propose a class of goodness of t tests based on Csiszar´s class of measures designed for heavy-tailed distributions.

Keywords

reliability theory; remaining life assessment; statistical distributions; statistical testing; Csiszar measure class; divergence measures; even-past lifetime evaluation; event residual lifetime evaluation; goodness of fit tests; heavy-tailed distributions; reliability engineering; statistical inference; technical systems; Distribution functions; Probability density function; Random variables; Reliability engineering; Shape; Time measurement; Heavy-tailed distributions; divergence measures; goodness of fit tests; reliability engineering;

fLanguage

English

Publisher

ieee

Conference_Titel

Availability, Reliability and Security (ARES), 2014 Ninth International Conference on

Conference_Location

Fribourg

Type

conf

DOI

10.1109/ARES.2014.62

Filename

6980311