Testing linearity in the single functional index model for dependent data

Kwo Lik CHAN; Aldo GOIA

Testing linearity in the single functional index model for dependent data

Dipartimento di Studi per l'Economia e l'Impresa

Risultato della ricerca: Capitolo in libro/report/atti di convegno › Contributo in volume (Capitolo o Saggio) › peer review

Abstract

Motivated by checking the linearity assumption in the regression model with functional covariate and real response in the case of dependent data, a new test for the single functional index model is introduced. The critical region of the test is derived by a bootstrap procedure. The finite sample performances of the test are evaluated by a simulation study and an application in the framework of functional time series forecasting is performed.

Lingua originale	Inglese
Titolo della pubblicazione ospite	14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023)
Editore	Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi
Pagine	45-53
Numero di pagine	9
ISBN (stampa)	978-3-031-84702-8
Stato di pubblicazione	Pubblicato - 2025

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https://hdl.handle.net/11579/186622

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CHAN, K. L., & GOIA, A. (2025). Testing linearity in the single functional index model for dependent data. In 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023) (pagg. 45-53). Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi. https://hdl.handle.net/11579/186622

CHAN, Kwo Lik ; GOIA, Aldo. / Testing linearity in the single functional index model for dependent data. 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023). Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi, 2025. pagg. 45-53

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abstract = "Motivated by checking the linearity assumption in the regression model with functional covariate and real response in the case of dependent data, a new test for the single functional index model is introduced. The critical region of the test is derived by a bootstrap procedure. The finite sample performances of the test are evaluated by a simulation study and an application in the framework of functional time series forecasting is performed.",

author = "CHAN, \{Kwo Lik\} and Aldo GOIA",

year = "2025",

language = "English",

isbn = "978-3-031-84702-8",

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booktitle = "14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023)",

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CHAN, KL & GOIA, A 2025, Testing linearity in the single functional index model for dependent data. in 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023). Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi, pagg. 45-53. <https://hdl.handle.net/11579/186622>

Testing linearity in the single functional index model for dependent data. / CHAN, Kwo Lik ; GOIA, Aldo.
14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023). Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi, 2025. pag. 45-53.

Risultato della ricerca: Capitolo in libro/report/atti di convegno › Contributo in volume (Capitolo o Saggio) › peer review

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AU - CHAN, Kwo Lik

AU - GOIA, Aldo

PY - 2025

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N2 - Motivated by checking the linearity assumption in the regression model with functional covariate and real response in the case of dependent data, a new test for the single functional index model is introduced. The critical region of the test is derived by a bootstrap procedure. The finite sample performances of the test are evaluated by a simulation study and an application in the framework of functional time series forecasting is performed.

AB - Motivated by checking the linearity assumption in the regression model with functional covariate and real response in the case of dependent data, a new test for the single functional index model is introduced. The critical region of the test is derived by a bootstrap procedure. The finite sample performances of the test are evaluated by a simulation study and an application in the framework of functional time series forecasting is performed.

UR - https://iris.uniupo.it/handle/11579/186622

M3 - Chapter

SN - 978-3-031-84702-8

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EP - 53

BT - 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023)

PB - Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi

ER -

CHAN KL , GOIA A. Testing linearity in the single functional index model for dependent data. In 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Volume: Statistical Models and Learning Methods for Complex Data (CLADAG 2023). Giuseppe Giordano, Michele La Rocca, Marcella Niglio, Marialuisa Restaino, Maurizio Vichi. 2025. pag. 45-53

Testing linearity in the single functional index model for dependent data

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