Sparse Semi-Functional Partial Linear Single-Index Regression

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http://hdl.handle.net/2183/21126Collections
- Investigación (FIC) [1654]
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Sparse Semi-Functional Partial Linear Single-Index RegressionDate
2018-09-17Citation
Novo, S.; Aneiros, G.; Vieu, P. Sparse Semi-Functional Partial Linear Single-Index Regression. Proceedings 2018, 2, 1190.
Abstract
[Abstract] The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure is employed for this task. Some properties of the resultant estimators are derived: the existence (and rate of convergence) of a consistent estimator for the parameters in the linear part and an oracle property for the variable selection method. Finally, a real data application illustrates the good performance of our procedure.
Keywords
Functional data analysis
Variable selection
Sparse model
Dimension reduction
Functional single-index model
Semiparametric model
Variable selection
Sparse model
Dimension reduction
Functional single-index model
Semiparametric model
Description
Trátase dun resumo estendido da ponencia
Editor version
Rights
Atribución 3.0 España
ISSN
2504-3900