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Adaptive group bridge estimation for high-dimensional partially linear models

This paper studies group selection for the partially linear model with a diverging number of parameters. We propose an adaptive group bridge method and study the consistency, convergence rate and asymptotic distribution of the global adaptive group bridge estimator under regularity conditions. Simul...

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Detalles Bibliográficos
Autores principales: Wang, Xiuli, Wang, Mingqiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493733/
https://www.ncbi.nlm.nih.gov/pubmed/28725135
http://dx.doi.org/10.1186/s13660-017-1432-x
Descripción
Sumario:This paper studies group selection for the partially linear model with a diverging number of parameters. We propose an adaptive group bridge method and study the consistency, convergence rate and asymptotic distribution of the global adaptive group bridge estimator under regularity conditions. Simulation studies and a real example show the finite sample performance of our method.