Related references
Note: Only part of the references are listed.WHICH BRIDGE ESTIMATOR IS THE BEST FOR VARIABLE SELECTION?
Shuaiwen Wang et al.
ANNALS OF STATISTICS (2020)
Hard thresholding regression
Qiang Sun et al.
SCANDINAVIAN JOURNAL OF STATISTICS (2019)
An Introduction to Second-Generation p-Values
Jeffrey D. Blume et al.
AMERICAN STATISTICIAN (2019)
Variable selection - A review and recommendations for the practicing statistician
Georg Heinze et al.
BIOMETRICAL JOURNAL (2018)
Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses
Jeffrey D. Blume et al.
PLOS ONE (2018)
Quantile universal threshold
Caroline Giacobino et al.
ELECTRONIC JOURNAL OF STATISTICS (2017)
Outcome-adaptive lasso: Variable selection for causal inference
Susan M. Shortreed et al.
BIOMETRICS (2017)
A Novel Machine Learning Model for Estimation of Sale Prices of Real Estate Units
Mohammad Hossein Rafiei et al.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2016)
A Novel Machine Learning Model for Estimation of Sale Prices of Real Estate Units
Mohammad Hossein Rafiei et al.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2016)
SLOPE-ADAPTIVE VARIABLE SELECTION VIA CONVEX OPTIMIZATION
Malgorzata Bogdan et al.
ANNALS OF APPLIED STATISTICS (2015)
Effective degrees of freedom: a flawed metaphor
Lucas Janson et al.
BIOMETRIKA (2015)
When does more regularization imply fewer degrees of freedom? Sufficient conditions and counterexamples
S. Kaufman et al.
BIOMETRIKA (2014)
High dimensional thresholded regression and shrinkage effect
Zemin Zheng et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2014)
CALIBRATING NONCONVEX PENALIZED REGRESSION IN ULTRA-HIGH DIMENSION
Lan Wang et al.
ANNALS OF STATISTICS (2013)
Asymptotic Equivalence of Regularization Methods in Thresholded Parameter Space
Yingying Fan et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2013)
Tuning parameter selection in high dimensional penalized likelihood
Yingying Fan et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2013)
Nonconcave Penalized Likelihood With NP-Dimensionality
Jianqing Fan et al.
IEEE TRANSACTIONS ON INFORMATION THEORY (2011)
The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso)
Sara van de Geer et al.
ELECTRONIC JOURNAL OF STATISTICS (2011)
NEARLY UNBIASED VARIABLE SELECTION UNDER MINIMAX CONCAVE PENALTY
Cun-Hui Zhang
ANNALS OF STATISTICS (2010)
Some sharp performance bounds for least squares regression with L1 regularization
Tong Zhang
ANNALS OF STATISTICS (2009)
HIGH-DIMENSIONAL VARIABLE SELECTION
Larry Wasserman et al.
ANNALS OF STATISTICS (2009)
LASSO-TYPE RECOVERY OF SPARSE REPRESENTATIONS FOR HIGH-DIMENSIONAL DATA
Nicolai Meinshausen et al.
ANNALS OF STATISTICS (2009)
Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting
Martin J. Wainwright
IEEE TRANSACTIONS ON INFORMATION THEORY (2009)
Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using l1-Constrained Quadratic Programming (Lasso)
Martin J. Wainwright
IEEE TRANSACTIONS ON INFORMATION THEORY (2009)
Forward Regression for Ultra-High Dimensional Variable Screening
Hansheng Wang
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2009)
Sure independence screening for ultrahigh dimensional feature space
Jianqing Fan et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2008)
Relaxed lasso
Nicolai Meinshausen
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2007)
The adaptive lasso and its oracle properties
Hui Zou
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2006)
High-dimensional graphs and variable selection with the Lasso
Nicolai Meinshausen et al.
ANNALS OF STATISTICS (2006)
Variable selection via nonconcave penalized likelihood and its oracle properties
JQ Fan et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2001)
Share Paper
