Estimation, imputation and prediction for the functional linear model with scalar response with responses missing at random

Febrero Bande, Manuel; Galeano San Miguel, Pedro; Gonzalez-Manteiga ., Wenceslao

Estimation, imputation and prediction for the functional linear model with scalar response with responses missing at random

Author(s): Febrero Bande, Manuel; Galeano San Miguel, Pedro; Gonzalez-Manteiga ., Wenceslao

Publisher: Elsevier

Issued date: 2019-03-01

Citation: Febrero-Bande, M., Galeano, P., & González-Manteiga, W. (2019). Estimation, imputation and prediction for the functional linear model with scalar response with responses missing at random. Computational Statistics & Data Analysis, 131, pp. 91-103.

ISSN: 0167-9473

DOI: https://doi.org/10.1016/j.csda.2018.07.006

xmlui.dri2xhtml.METS-1.0.item-contributor-funder: Ministerio de Economía y Competitividad (España)

Sponsor: The first and third author acknowledge financial support from Ministerio de Economía y Competitividad grant MTM2013-41383-P and MTM2016-76969-P. The second author acknowledges financial support from Ministerio de Economía y Competitividad grant ECO2015-66593-P

Project: Gobierno de España. ECO2015-66593-P
Gobierno de España. MTM2013-41383-P
Gobierno de España. MTM2016-76969-P

Keywords: Functional Linear Model , Imputation of missing responses , Mean square error of estimation , Mean square error of prediction , Missing at random , Scalar response , Regression , Convergence , Rates

URI: http://hdl.handle.net/10016/35322

Rights: © 2018 Elsevier B.V. All rights reserved
Atribución-NoComercial-SinDerivadas 3.0 España

Abstract:

Two different methods for estimation, imputation and prediction for the functional linear model with scalar response when some of the responses are missing at random (MAR) are developed. The simplified method consists in estimating the model parameters using o [+]

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