Academic Journal
Nested functional ANOVA with pointwise and global inference: theory and application to COVID-Era financial data.
| Τίτλος: | Nested functional ANOVA with pointwise and global inference: theory and application to COVID-Era financial data. |
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| Συγγραφείς: | Celik, N.1 (AUTHOR) nuricelik@gtu.edu.tr |
| Πηγή: | Journal of Applied Statistics. Oct2026, Vol. 53 Issue 13, p2574-2589. 16p. |
| Θεματικοί όροι: | *Functional analysis, *Financial databases, Inferential statistics |
| Περίληψη: | We propose a nested functional analysis of variance (FANOVA) model to investigate hierarchical variation structures in functional data. The model extends classical ANOVA by incorporating both main effects and nested subgroup effects, allowing for the decomposition of functional variation across multiple levels. Model parameters are estimated using matrix-based representations under functional linear model assumptions. For hypothesis testing, we develop pointwise F-type statistics and global tests based on the $ L^2 $ L 2 norm of the effect functions, with null distributions approximated via Welch–Satterthwaite techniques. Through extensive simulation studies, we assess the accuracy of parameter estimation, control of Type I error, and power under various noise levels, sample sizes, and contamination scenarios. The methodology is further illustrated through an application to stock market index data from 24 countries during the COVID-19 pandemic, where we analyze regional and nested economic effects. The results demonstrate that the proposed nested FANOVA framework effectively captures structured functional variation and remains robust under a range of realistic data conditions. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Applied Statistics is the property of Taylor & Francis Ltd 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.) | |
| Βάση Δεδομένων: | Business Source Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:bsx&genre=article&issn=02664763&ISBN=&volume=53&issue=13&date=20261001&spage=2574&pages=2574-2589&title=Journal of Applied Statistics&atitle=Nested%20functional%20ANOVA%20with%20pointwise%20and%20global%20inference%3A%20theory%20and%20application%20to%20COVID-Era%20financial%20data.&aulast=Celik%2C%20N.&id=DOI:10.1080/02664763.2025.2606963 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: Nested functional ANOVA with pointwise and global inference: theory and application to COVID-Era financial data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Celik%2C+N%2E%22">Celik, N.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> nuricelik@gtu.edu.tr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Statistics%22">Journal of Applied Statistics</searchLink>. Oct2026, Vol. 53 Issue 13, p2574-2589. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Functional+analysis%22">Functional analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Financial+databases%22">Financial databases</searchLink><br /><searchLink fieldCode="DE" term="%22Inferential+statistics%22">Inferential statistics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We propose a nested functional analysis of variance (FANOVA) model to investigate hierarchical variation structures in functional data. The model extends classical ANOVA by incorporating both main effects and nested subgroup effects, allowing for the decomposition of functional variation across multiple levels. Model parameters are estimated using matrix-based representations under functional linear model assumptions. For hypothesis testing, we develop pointwise F-type statistics and global tests based on the $ L^2 $ L 2 norm of the effect functions, with null distributions approximated via Welch–Satterthwaite techniques. Through extensive simulation studies, we assess the accuracy of parameter estimation, control of Type I error, and power under various noise levels, sample sizes, and contamination scenarios. The methodology is further illustrated through an application to stock market index data from 24 countries during the COVID-19 pandemic, where we analyze regional and nested economic effects. The results demonstrate that the proposed nested FANOVA framework effectively captures structured functional variation and remains robust under a range of realistic data conditions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Applied Statistics is the property of Taylor & Francis Ltd 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: 10.1080/02664763.2025.2606963 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 2574 Subjects: – SubjectFull: Functional analysis Type: general – SubjectFull: Financial databases Type: general – SubjectFull: Inferential statistics Type: general Titles: – TitleFull: Nested functional ANOVA with pointwise and global inference: theory and application to COVID-Era financial data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Celik, N. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 02664763 Numbering: – Type: volume Value: 53 – Type: issue Value: 13 Titles: – TitleFull: Journal of Applied Statistics Type: main |
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