The circular quantile residual
Main Author: | |
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Publication Date: | 2023 |
Other Authors: | , |
Language: | eng |
Source: | Repositório Institucional da INSPER |
Download full: | https://repositorio.insper.edu.br/handle/11224/6632 |
Summary: | Circular-linear regression is often used to model the relationship between a circular dependent variable and a set of linear predictor variables. It is used in many areas such as meteorology, biology, and medicine. For checking model adequacy, it is desirable to use residuals that are approximately standard normally distributed. Most of the residuals used in circular regression models do not meet this requirement and are used especially for outlier identification. Other residuals are limited to the von Mises regression models. An asymptotically standard normally distributed residual that can be used for any parametric circular-linear regression model is introduced. Monte Carlo simulation studies suggest that the distribution of this residual is well approximated by the standard normal distribution in small samples. To study the behavior of this residual, two regression models are introduced, and two applications are used to show that the proposed residual can detect model misspecification. |
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The circular quantile residualCircular dataCircular-linear regression modelsDiagnostic analysisQuantile residualCircular-linear regression is often used to model the relationship between a circular dependent variable and a set of linear predictor variables. It is used in many areas such as meteorology, biology, and medicine. For checking model adequacy, it is desirable to use residuals that are approximately standard normally distributed. Most of the residuals used in circular regression models do not meet this requirement and are used especially for outlier identification. Other residuals are limited to the von Mises regression models. An asymptotically standard normally distributed residual that can be used for any parametric circular-linear regression model is introduced. Monte Carlo simulation studies suggest that the distribution of this residual is well approximated by the standard normal distribution in small samples. To study the behavior of this residual, two regression models are introduced, and two applications are used to show that the proposed residual can detect model misspecification.Elsevier2024-05-03T15:43:27Z2024-05-03T15:43:27Z2023Digital16 p.application/pdfapplication/pdf0167-94731872-7352https://repositorio.insper.edu.br/handle/11224/663210.1016/j.csda.2022.107612Computational Statistics & Data AnalysisProdução vinculada ao Núcleo de Ciências de Dados e DecisãoAndrade, Ana C.C.Pereira, Gustavo H.A.Andrade, Ana C.C.Pereira, Gustavo H.A.RINALDO ARTESinfo:eu-repo/semantics/publishedVersionengreponame:Repositório Institucional da INSPERinstname:Instituição de Ensino Superior e de Pesquisa (INSPER)instacron:INSPERinfo:eu-repo/semantics/openAccess2025-06-12T13:15:01Zoai:repositorio.insper.edu.br:11224/6632Biblioteca Digital de Teses e Dissertaçõeshttps://www.insper.edu.br/biblioteca-telles/PRIhttps://repositorio.insper.edu.br/oai/requestbiblioteca@insper.edu.br || conteudobiblioteca@insper.edu.bropendoar:2025-06-12T13:15:01Repositório Institucional da INSPER - Instituição de Ensino Superior e de Pesquisa (INSPER)false |
dc.title.none.fl_str_mv |
The circular quantile residual |
title |
The circular quantile residual |
spellingShingle |
The circular quantile residual Andrade, Ana C.C. Circular data Circular-linear regression models Diagnostic analysis Quantile residual |
title_short |
The circular quantile residual |
title_full |
The circular quantile residual |
title_fullStr |
The circular quantile residual |
title_full_unstemmed |
The circular quantile residual |
title_sort |
The circular quantile residual |
author |
Andrade, Ana C.C. |
author_facet |
Andrade, Ana C.C. Pereira, Gustavo H.A. RINALDO ARTES |
author_role |
author |
author2 |
Pereira, Gustavo H.A. RINALDO ARTES |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Andrade, Ana C.C. Pereira, Gustavo H.A. Andrade, Ana C.C. Pereira, Gustavo H.A. RINALDO ARTES |
dc.subject.por.fl_str_mv |
Circular data Circular-linear regression models Diagnostic analysis Quantile residual |
topic |
Circular data Circular-linear regression models Diagnostic analysis Quantile residual |
description |
Circular-linear regression is often used to model the relationship between a circular dependent variable and a set of linear predictor variables. It is used in many areas such as meteorology, biology, and medicine. For checking model adequacy, it is desirable to use residuals that are approximately standard normally distributed. Most of the residuals used in circular regression models do not meet this requirement and are used especially for outlier identification. Other residuals are limited to the von Mises regression models. An asymptotically standard normally distributed residual that can be used for any parametric circular-linear regression model is introduced. Monte Carlo simulation studies suggest that the distribution of this residual is well approximated by the standard normal distribution in small samples. To study the behavior of this residual, two regression models are introduced, and two applications are used to show that the proposed residual can detect model misspecification. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2024-05-03T15:43:27Z 2024-05-03T15:43:27Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
0167-9473 1872-7352 https://repositorio.insper.edu.br/handle/11224/6632 10.1016/j.csda.2022.107612 |
identifier_str_mv |
0167-9473 1872-7352 10.1016/j.csda.2022.107612 |
url |
https://repositorio.insper.edu.br/handle/11224/6632 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Computational Statistics & Data Analysis Produção vinculada ao Núcleo de Ciências de Dados e Decisão |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
Digital 16 p. application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da INSPER instname:Instituição de Ensino Superior e de Pesquisa (INSPER) instacron:INSPER |
instname_str |
Instituição de Ensino Superior e de Pesquisa (INSPER) |
instacron_str |
INSPER |
institution |
INSPER |
reponame_str |
Repositório Institucional da INSPER |
collection |
Repositório Institucional da INSPER |
repository.name.fl_str_mv |
Repositório Institucional da INSPER - Instituição de Ensino Superior e de Pesquisa (INSPER) |
repository.mail.fl_str_mv |
biblioteca@insper.edu.br || conteudobiblioteca@insper.edu.br |
_version_ |
1839074950463356928 |