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المؤلفBeyaztas, Ufuk
المؤلفShang, Han Lin
المؤلفAbdel-Salam, Abdel Salam G.
تاريخ الإتاحة2022-08-24T07:52:49Z
تاريخ النشر2022-01-01
اسم المنشورCommunications in Statistics: Simulation and Computation
المعرّفhttp://dx.doi.org/10.1080/03610918.2020.1714662
الاقتباسUfuk 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
الرقم المعياري الدولي للكتاب03610918
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078499799&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/33402
الملخصAggregation 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.
اللغةen
الناشرTaylor and Francis Group
الموضوعFunctional data
interval-valued data
maximum likelihood
regression
العنوانFunctional linear models for interval-valued data
النوعArticle
الصفحات3513-3532
رقم العدد7
رقم المجلد51
ESSN1532-4141
dc.accessType Abstract Only


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