Rights statement: This is the author’s version of a work that was accepted for publication in Statistics & Probability Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Statistics & Probability Letters, 122, 2016 DOI: 10.1016/j.spl.2016.10.032
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Computation of an exact confidence set for a maximum point of a univariate polynomial function in a given interval
AU - Zhou, Sanyu
AU - Wan, Fang
AU - Liu, Wei
AU - Bretz, Frank
N1 - This is the author’s version of a work that was accepted for publication in Statistics & Probability Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Statistics & Probability Letters, 122, 2016 DOI: 10.1016/j.spl.2016.10.032
PY - 2017/3
Y1 - 2017/3
N2 - 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−α1−α 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.
AB - 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−α1−α 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.
KW - Confidence set
KW - Numerical quadrature
KW - P-value
KW - Statistical inference
KW - Parametric regression
KW - Semi-parametric regression
U2 - 10.1016/j.spl.2016.10.032
DO - 10.1016/j.spl.2016.10.032
M3 - Journal article
VL - 122
SP - 157
EP - 161
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
ER -