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The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications
In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit generalized half-normal distribution, we get the interpretation of its location parameter as being a quantile of the distribution. In addition, we can ev...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331020/ https://www.ncbi.nlm.nih.gov/pubmed/35915830 http://dx.doi.org/10.1007/s00500-022-07278-3 |
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author | Mazucheli, Josmar Korkmaz, Mustafa Ç. Menezes, André F. B. Leiva, Víctor |
author_facet | Mazucheli, Josmar Korkmaz, Mustafa Ç. Menezes, André F. B. Leiva, Víctor |
author_sort | Mazucheli, Josmar |
collection | PubMed |
description | In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit generalized half-normal distribution, we get the interpretation of its location parameter as being a quantile of the distribution. In addition, we can evaluate effects of the explanatory variables in the conditional quantiles of the response variable as an alternative to the Kumaraswamy quantile regression model. The suitability of our proposal is demonstrated with two simulated examples and two real applications. For such data sets, the obtained fits of the proposed regression model are compared with that provided by a Kumaraswamy regression model. |
format | Online Article Text |
id | pubmed-9331020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-93310202022-07-28 The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications Mazucheli, Josmar Korkmaz, Mustafa Ç. Menezes, André F. B. Leiva, Víctor Soft comput Mathematical Methods in Data Science In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit generalized half-normal distribution, we get the interpretation of its location parameter as being a quantile of the distribution. In addition, we can evaluate effects of the explanatory variables in the conditional quantiles of the response variable as an alternative to the Kumaraswamy quantile regression model. The suitability of our proposal is demonstrated with two simulated examples and two real applications. For such data sets, the obtained fits of the proposed regression model are compared with that provided by a Kumaraswamy regression model. Springer Berlin Heidelberg 2022-07-27 2023 /pmc/articles/PMC9331020/ /pubmed/35915830 http://dx.doi.org/10.1007/s00500-022-07278-3 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.corrected publication 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Mathematical Methods in Data Science Mazucheli, Josmar Korkmaz, Mustafa Ç. Menezes, André F. B. Leiva, Víctor The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title | The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title_full | The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title_fullStr | The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title_full_unstemmed | The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title_short | The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
title_sort | unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications |
topic | Mathematical Methods in Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9331020/ https://www.ncbi.nlm.nih.gov/pubmed/35915830 http://dx.doi.org/10.1007/s00500-022-07278-3 |
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