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A location invariant moment-type estimator. I
Author(s):
Cheng-Xiu
Ling;
Zuoxiang
Peng;
Saralees
Nadarajah
Original publication:
Teoriya Imovirnostei ta Matematichna Statistika,
vipusk 76
(2007).
Journal:
Theor. Probability and Math. Statist.
No. 76
(2008),
23-31.
MSC (2000):
Primary 60F99
Posted:
July 10, 2008
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Additional information
Abstract:
The moment's estimator (Dekkers et al., 1989) has been used in extreme value theory to estimate the tail index, but it is not location invariant. The location invariant Hill-type estimator (Fraga Alves, 2001) is only suitable to estimate positive indices. In this paper, a new moment-type estimator is studied, which is location invariant. This new estimator is based on the original moment-type estimator, but is made location invariant by a random shift. Its weak consistency and strong consistency are derived, in a semiparametric setup.
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Additional Information:
Cheng-Xiu
Ling
Affiliation:
Department of Mathematics, Southwest Normal University, Chongqing 400715, P. R. China
Email:
pzx@swu.edu.cn
Zuoxiang
Peng
Affiliation:
Department of Mathematics, Southwest Normal University, Chongqing 400715, P. R. China
Saralees
Nadarajah
Affiliation:
Department of Statistics, University of Nebraska-Lincoln, Lincoln, Nebraska 68583, USA
Email:
snadaraj@unlserve.unl.edu
DOI:
10.1090/S0094-9000-08-00728-X
PII:
S 0094-9000(08)00728-X
Keywords:
Extreme value index,
location invariant property,
moment estimation,
strong and weak consistencies,
order statistics,
regular varying functions
Received by editor(s):
29/NOV/2005
Posted:
July 10, 2008
Copyright of article:
Copyright
2008,
American Mathematical Society
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