Sequential profile Lasso for ultra-high-dimensional partially linear models

In this paper, we study ultra-high-dimensional partially linear models when the dimension of the linear predictors grows exponentially with the sample size. For the variable screening, we propose a sequential profile Lasso method (SPLasso) and show that it possesses the screening property. SPLasso c...

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Principais autores:	Yujie Li, Gaorong Li, Tiejun Tong
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Taylor & Francis Group 2017-07-01
סדרה:	Statistical Theory and Related Fields
נושאים:	sequential profile lasso partially linear model extended bayesian information criterion screening property ultra-high-dimensional data
גישה מקוונת:	http://dx.doi.org/10.1080/24754269.2017.1396432
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