Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/70495
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Tail-adaptive Location Rank Test for the Generalized Secant Hyperbolic Distribution |
Author: | Kravchuk, O. Hu, J. |
Citation: | Communications in Statistics: Simulation and Computation, 2008; 37(6):1052-1063 |
Publisher: | Marcel Dekker Inc |
Issue Date: | 2008 |
ISSN: | 0361-0918 1532-4141 |
Statement of Responsibility: | O. Y. Kravchuk and J. Hu |
Abstract: | The generalized secant hyperbolic distribution (GSHD) was recently introduced as a modeling tool in data analysis. The GSHD is a unimodal distribution that is completely specified by location, scale, and shape parameters. It has also been shown elsewhere that the rank procedures of location are regular, robust, and asymptotically fully efficient. In this article, we study certain tail weight measures for the GSHD and introduce a tail-adaptive rank procedure of location based on those tail weight measures. We investigate the properties of the new adaptive rank procedure and compare it to some conventional estimators. |
Keywords: | Adaptive rank estimator Generalized secant hyperbolic distribution location problem tail weight |
Rights: | Copyright © Taylor & Francis Group, LLC |
DOI: | 10.1080/03610910802049490 |
Published version: | http://dx.doi.org/10.1080/03610910802049490 |
Appears in Collections: | Agriculture, Food and Wine publications Aurora harvest |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.