Heavy-tailed exponential distribution: Basic properties and parameter estimation

Zengguo Sun, Chongzhao Han, Ram Mohan Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Heavy-tailed exponential distribution is a direct and necessary extension of the heavy-tailed Rayleigh distribution. First, some basic properties of heavy-tailed exponential distribution are introduced in this paper including the series form of the density function, the heavy-tailed property and the nonexistence of finite variance. Second, ratio estimator, logarithmic moment estimator and iterative logarithmic moment estimator are presented to estimate the parameters of heavy-tailed exponential distribution based on negative-order moments. The logarithmic moment estimator with explicit closed form is only determined by samples, and the iterative logarithmic moment estimator achieves better performance only using fewer samples in each step computation. Monte Carlo simulation results demonstrate the high efficiency of the iterative logarithmic moment estimator for heavytailed exponential distribution.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th International Conference on Information Fusion, FUSION 2008
DOIs
Publication statusPublished - 2008
Event11th International Conference on Information Fusion, FUSION 2008 - Cologne, Germany
Duration: Jun 30 2008Jul 3 2008

Other

Other11th International Conference on Information Fusion, FUSION 2008
CountryGermany
CityCologne
Period6/30/087/3/08

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

Sun, Z., Han, C., & Narayanan, R. M. (2008). Heavy-tailed exponential distribution: Basic properties and parameter estimation. In Proceedings of the 11th International Conference on Information Fusion, FUSION 2008 [4632306] https://doi.org/10.1109/ICIF.2008.4632306