Influential observations detection in the gamma-pareto regression model under different link functions with standardized and adjusted deviance residuals: simulation and application.
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| Title: | Influential observations detection in the gamma-pareto regression model under different link functions with standardized and adjusted deviance residuals: simulation and application. |
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| Authors: | SALEEM, Nasir1 nasirsaleem160@gmail.com, AKBAR, Atif1, LAEEQ, Saima2, AHMAD, Shakeel1, Herlina HANUM3 |
| Source: | Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi. Jun2025, Vol. 43 Issue 3, p760-776. 17p. |
| Subjects: | Inverse functions, Regression analysis, Sample size (Statistics), Dispersion (Chemistry), Performance theory |
| Abstract: | This study compares the performance of link functions for diagnostic methods to diagnose influential observations in the Gamma-Pareto regression model (G-PRM). Three link functions, i.e. inverse, identity, and log are considered to identify which link function gives the best results. For our investigation, we employed standardized deviance residuals (SDR) and adjusted deviance residuals (ADR). We used Cook's distance (CD) and Difference of fit (DIFFITS) as diagnostic methods. We compare the performance of influence diagnostics with the link functions using the simulation study and a real-life application. Results show that the CD with the log link function is a good method for small dispersion. For large dispersion and small sample sizes, the performance of the DIFFITS with inverse and identity link functions is better than the CD method. Similarly, for large dispersion and sample sizes, the CD (with identity and log link functions) and DFFITS with inverse link function give the same performance. [ABSTRACT FROM AUTHOR] |
| Copyright of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi is the property of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186360441 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Influential observations detection in the gamma-pareto regression model under different link functions with standardized and adjusted deviance residuals: simulation and application. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22SALEEM%2C+Nasir%22">SALEEM, Nasir</searchLink><relatesTo>1</relatesTo><i> nasirsaleem160@gmail.com</i><br /><searchLink fieldCode="AR" term="%22AKBAR%2C+Atif%22">AKBAR, Atif</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22LAEEQ%2C+Saima%22">LAEEQ, Saima</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22AHMAD%2C+Shakeel%22">AHMAD, Shakeel</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Herlina+HANUM%22">Herlina HANUM</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sigma%3A+Journal+of+Engineering+%26+Natural+Sciences+%2F+Mühendislik+ve+Fen+Bilimleri+Dergisi%22">Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi</searchLink>. Jun2025, Vol. 43 Issue 3, p760-776. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Inverse+functions%22">Inverse functions</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Sample+size+%28Statistics%29%22">Sample size (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Dispersion+%28Chemistry%29%22">Dispersion (Chemistry)</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+theory%22">Performance theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study compares the performance of link functions for diagnostic methods to diagnose influential observations in the Gamma-Pareto regression model (G-PRM). Three link functions, i.e. inverse, identity, and log are considered to identify which link function gives the best results. For our investigation, we employed standardized deviance residuals (SDR) and adjusted deviance residuals (ADR). We used Cook's distance (CD) and Difference of fit (DIFFITS) as diagnostic methods. We compare the performance of influence diagnostics with the link functions using the simulation study and a real-life application. Results show that the CD with the log link function is a good method for small dispersion. For large dispersion and small sample sizes, the performance of the DIFFITS with inverse and identity link functions is better than the CD method. Similarly, for large dispersion and sample sizes, the CD (with identity and log link functions) and DFFITS with inverse link function give the same performance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi is the property of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.14744/sigma.2025.00070 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 760 Subjects: – SubjectFull: Inverse functions Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Sample size (Statistics) Type: general – SubjectFull: Dispersion (Chemistry) Type: general – SubjectFull: Performance theory Type: general Titles: – TitleFull: Influential observations detection in the gamma-pareto regression model under different link functions with standardized and adjusted deviance residuals: simulation and application. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: SALEEM, Nasir – PersonEntity: Name: NameFull: AKBAR, Atif – PersonEntity: Name: NameFull: LAEEQ, Saima – PersonEntity: Name: NameFull: AHMAD, Shakeel – PersonEntity: Name: NameFull: Herlina HANUM IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13047191 Numbering: – Type: volume Value: 43 – Type: issue Value: 3 Titles: – TitleFull: Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi Type: main |
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