Computation of an exact confidence set for a maximum point of a univariate polynomial function in a given interval
Computation of an exact confidence set for a maximum point of a univariate polynomial function in a given interval
Construction of a confidence set for a maximum point of a function is an important statistical problem. Wan et al. (2015) provided an exact 1??1?? confidence set for a maximum point of a univariate polynomial function in a given interval. In this paper, we give an efficient computational method for computing the confidence set of Wan et al. (2015). We demonstrate with two examples that the new method is substantially more efficient than the proposals by Wan et al. (2015). Matlab programs have been written which make the implementation of the new method straightforward.
157-161
Zhou, Sanyu
8b006abb-cfc9-4099-94b3-a6f9a034decf
Wan, Fang
2d1357dd-b94d-418f-a721-e0e95909e39c
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0
March 2017
Zhou, Sanyu
8b006abb-cfc9-4099-94b3-a6f9a034decf
Wan, Fang
2d1357dd-b94d-418f-a721-e0e95909e39c
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0
Zhou, Sanyu, Wan, Fang, Liu, Wei and Bretz, Frank
(2017)
Computation of an exact confidence set for a maximum point of a univariate polynomial function in a given interval.
Statistics & Probability Letters, 122, .
(doi:10.1016/j.spl.2016.10.032).
Abstract
Construction of a confidence set for a maximum point of a function is an important statistical problem. Wan et al. (2015) provided an exact 1??1?? confidence set for a maximum point of a univariate polynomial function in a given interval. In this paper, we give an efficient computational method for computing the confidence set of Wan et al. (2015). We demonstrate with two examples that the new method is substantially more efficient than the proposals by Wan et al. (2015). Matlab programs have been written which make the implementation of the new method straightforward.
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Accepted/In Press date: 31 October 2016
e-pub ahead of print date: 18 November 2016
Published date: March 2017
Organisations:
Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 404556
URI: http://eprints.soton.ac.uk/id/eprint/404556
ISSN: 0167-7152
PURE UUID: 010899d7-bdee-41fc-a7cf-d03aaf666cfc
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Date deposited: 11 Jan 2017 14:32
Last modified: 16 Mar 2024 02:42
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Contributors
Author:
Sanyu Zhou
Author:
Fang Wan
Author:
Frank Bretz
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