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A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry
In this note we provide a novel semi-parametric best linear unbiased estimator (BLUE) of location and its corresponding variance estimator under the assumption the random variate is generated from a symmetric location-scale family of distributions. The approach follows in a two-stage fashion and is...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678347/ https://www.ncbi.nlm.nih.gov/pubmed/36415761 http://dx.doi.org/10.1080/03610918.2020.1769131 |
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author | Hutson, Alan D. |
author_facet | Hutson, Alan D. |
author_sort | Hutson, Alan D. |
collection | PubMed |
description | In this note we provide a novel semi-parametric best linear unbiased estimator (BLUE) of location and its corresponding variance estimator under the assumption the random variate is generated from a symmetric location-scale family of distributions. The approach follows in a two-stage fashion and is based on the exact bootstrap estimate of the covariance matrix of the order statistic. We generalize our approach to add a robustness component in order to derive a trimmed BLUE of location under a semi-parametric symmetry assumption. |
format | Online Article Text |
id | pubmed-9678347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-96783472022-11-21 A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry Hutson, Alan D. Commun Stat Simul Comput Article In this note we provide a novel semi-parametric best linear unbiased estimator (BLUE) of location and its corresponding variance estimator under the assumption the random variate is generated from a symmetric location-scale family of distributions. The approach follows in a two-stage fashion and is based on the exact bootstrap estimate of the covariance matrix of the order statistic. We generalize our approach to add a robustness component in order to derive a trimmed BLUE of location under a semi-parametric symmetry assumption. 2022 2020-06-01 /pmc/articles/PMC9678347/ /pubmed/36415761 http://dx.doi.org/10.1080/03610918.2020.1769131 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
spellingShingle | Article Hutson, Alan D. A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title | A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title_full | A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title_fullStr | A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title_full_unstemmed | A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title_short | A semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
title_sort | semi-parametric bootstrap-based best linear unbiased estimator of location under symmetry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678347/ https://www.ncbi.nlm.nih.gov/pubmed/36415761 http://dx.doi.org/10.1080/03610918.2020.1769131 |
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