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SCAD-penalized regression in high-dimensional partially linear models

https://doi.org/10.1214/07-aos580
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Spline Smoothing in a Partly Linear Model
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Kernel Smoothing in Partial Linear Models
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Regression Shrinkage and Selection Via the Lasso
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Spline Models for Observational Data
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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
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New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
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Nonconcave penalized likelihood with a diverging number of parameters
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Variable selection using MM algorithms
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High-dimensional graphs and variable selection with the Lasso
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Asymptotic properties of bridge estimators in sparse high-dimensional regression models
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High-dimensional generalized linear models and the lasso
inferredcites →https://doi.org/10.1214/07-aos520openalex-snapshot
The sparsity and bias of the Lasso selection in high-dimensional linear regression
inferredcites →https://doi.org/10.1214/aos/1015957397openalex-snapshot
Asymptotics for lasso-type estimators
inferredcites →https://doi.org/10.1214/aos/1017939141openalex-snapshot
Efficient estimation of the partly linear additive Cox model
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Optimal Rates of Convergence for Nonparametric Estimators
inferredcites →https://doi.org/10.1214/aos/1176345969openalex-snapshot
Optimal Global Rates of Convergence for Nonparametric Regression
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Multivariate Adaptive Regression Splines
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Additive Regression and Other Nonparametric Models
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Convergence Rates for Parametric Components in a Partly Linear Model
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Root-N-Consistent Semiparametric Regression

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Robust Variable Selection Based on High-Dimensional Partial Linear Model of Elastic Net Penalty
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An efficient algorithm for the non-convex penalized multinomial logistic regression
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Using Regularized Methods to Validate Q-Matrix in Cognitive Diagnostic Assessment
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First-Order Algorithms for Nonlinear Structured Optimization
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Minimax optimal estimation in partially linear additive models under high dimension
inferred← citeshttps://doi.org/10.3150/24-bej1847openalex-snapshot
High-dimensional partially linear additive models on Riemannian manifolds
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Statistical Inference for High-Dimensional Heteroscedastic Partially Single-Index Models
inferred← citeshttps://doi.org/10.3390/math10234532openalex-snapshot
A Double Penalty Model for Ensemble Learning
inferred← citeshttps://doi.org/10.3390/math10244767openalex-snapshot
Application of the ADMM Algorithm for a High-Dimensional Partially Linear Model
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Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data
inferred← citeshttps://doi.org/10.3390/math11194220openalex-snapshot
Application of LADMM and As-LADMM for a High-Dimensional Partially Linear Model
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Estimation and Variable Selection in Sequential Linear Models: SCAD-Penalized Method with Applications
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Inconsistency of Classical Penalized Likelihood Approaches under Endogeneity
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Double-Penalized Quantile Regression in Partially Linear Models
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Penalized LAD-SCAD Estimator Based on Robust Wrapped Correlation Screening Method for High Dimensional Models
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Profiled forward regression for ultrahigh dimensional variable screening in semiparametric partially linear models
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Efficient Bayesian High-Dimensional Classification via Random Projection with Application to Gene Expression Data
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