Regression estimators for the tail index

AL-Najafi Amenah and Stachó László Lajos and Viharos László: Regression estimators for the tail index. In: Acta scientiarum mathematicarum, (87) 3-4. pp. 649-678. (2021)

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We propose a class of weighted least squares estimators for the tail index of a distribution function with a regularly varying tail. Our approach is based on the method developed by Holan and McElroy (2010) for the Parzen tail index. We prove asymptotic normality and consistency for the estimators under suitable assumptions. These and earlier estimators are compared in various models through a simulation study using the mean squared error as criterion. The results show that the weighted least squares estimator has good performance.

Item Type: Article
Heading title: Probability theory
Journal or Publication Title: Acta scientiarum mathematicarum
Date: 2021
Volume: 87
Number: 3-4
ISSN: 2064-8316
Page Range: pp. 649-678
Language: English
Place of Publication: Szeged
Related URLs:
DOI: 10.14232/actasm-020-361-6
Uncontrolled Keywords: Valószínűségszámítás
Additional Information: Bibliogr.: 678. p. ; ill. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.01. Mathematics
Date Deposited: 2022. May. 24. 13:55
Last Modified: 2022. May. 24. 13:55

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