High dimensional variable selection. Annals of statis- tics, 37(5A):2178-2201, January 2009.L. Wasserman and K. Roeder. High dimensional variable selection. Annals of statistics, 37(5A):2178, 2009.Wasserman L, Roeder K. 2009. High dimensional variable selection. Annal Stat 37:2178-2201....
Variable selection in high-dimensional partly linear additive models, J. Nonparametric Statist., 24(4), 825-839.Lian H (2012) Variable selection in high-dimensional partly linear additive models. J Nonparametr Stat 24:825-839.Lian, H. (2012). Variable selection in hight-dimensional partly ...
The variable selection problem is discussed in the context of high-dimensional failure time data arising from the accelerated failure time model. A data augmentation approach is employed in order to deal with censored survival times and to facilitate prior-posterior conjugacy. To identify a set of ...
We study the problem of high-dimensional variable selection via some two-step procedures. First we show that given some good initial estimator which is $\\ell_{\\infty}$-consistent but not necessarily variable selection consistent, we can apply the nonnegative Garrote, adaptive Lasso or hard-...
订购 Ji, Pengsheng. Cornell University ProQuest Dissertations & Theses, 2012. 3531031. 隐私偏好中心 您的隐私 绝对必要的 Cookie 功能Cookie 定向Cookie 社交媒体 Cookie 性能Cookie 您的隐私 您访问任何网站时,网站都可能在您的浏览器上存储或检索信息,大多数是以 Cookie 的形式进行。此信息可能...
High-dimensionallongitudinal data arise frequently in biomedical and genomic research. It isimportant to select relevant covariates when the dimension of the parametersdiverges as the sample sizeincreases. We consider the problem of variable selection in high-dimensionallinear models with longitudinal data....
摘要: In this paper, we consider the problem of variable selection for high-dimensional generalized varying-coefficient models and propose a polynomial-spline based procedure that simultaneously eliminates irrelevant predictors and estimates the nonzero coefficients. In a 关键词: Diverging parameters group...
In Section 2, we propose a split-and-conquer variable selection procedure for high-dimensional general semiparametric models with massive data, and establish selection consistency and the oracle property of the proposed method. In Section 3, we propose a computational algorithm to solve the penalized...
Disagreement based variable selection method for high-dimensional censored data hasinur@isrt.ac.bdMd Hasinur Rahaman KhanSuborna Sultana
Tight conditions for consistent variable selection in high dimensional nonparametric regression - Comminges, Dalalyan - 2011 () Citation Context ...tically minimax with Tn,γ ∼ (r ∗ n,γ )−2 (1+2κ −1 ). hal-00722903, version 3 - 3 Jan 2013 Remark 6. The previous result ...