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AuthorBeyaztas, Ufuk
AuthorShang, Han Lin
AuthorAbdel-Salam, Abdel Salam G.
Available date2022-08-24T07:52:49Z
Publication Date2022-01-01
Publication NameCommunications in Statistics: Simulation and Computation
Identifierhttp://dx.doi.org/10.1080/03610918.2020.1714662
CitationUfuk Beyaztas, Han Lin Shang & Abdel-Salam G. Abdel-Salam (2022) Functional linear models for interval-valued data, Communications in Statistics - Simulation and Computation, 51:7, 3513-3532, DOI: 10.1080/03610918.2020.1714662
ISSN03610918
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078499799&origin=inward
URIhttp://hdl.handle.net/10576/33402
AbstractAggregation of large databases in a specific format is a frequently used process to make the data easily manageable. Interval-valued data is one of the data types that is generated by such an aggregation process. Using traditional methods to analyze interval-valued data results in loss of information, and thus, several interval-valued data models have been proposed to gather reliable information from such data types. On the other hand, recent technological developments have led to high dimensional and complex data in many application areas, which may not be analyzed by traditional techniques. Functional data analysis is one of the most commonly used techniques to analyze such complex datasets. While the functional extensions of much traditional statistical techniques are available, the functional form of the interval-valued data has not been studied well. This article introduces the functional forms of some well-known regression models that take interval-valued data. The proposed methods are based on the function-on-function regression model, where both the response and predictor/s are functional. Through several Monte Carlo simulations and empirical data analysis, the finite sample performance of the proposed methods is evaluated and compared with the state-of-the-art.
Languageen
PublisherTaylor and Francis Group
SubjectFunctional data
interval-valued data
maximum likelihood
regression
TitleFunctional linear models for interval-valued data
TypeArticle
Pagination3513-3532
Issue Number7
Volume Number51
ESSN1532-4141
dc.accessType Abstract Only


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