Pages that link to "Item:Q1043712"

The following pages link to High-dimensional additive modeling (Q1043712):

Displaying 50 items.

• On density and regression estimation with incomplete data (Q4605247) (← links)
• Metamodel construction for sensitivity analysis (Q4606427) (← links)
• Tuning parameters in random forests (Q4606433) (← links)
• Impact of subsampling and tree depth on random forests (Q4615432) (← links)
• Sparse Additive Models (Q4632616) (← links)
• Semiparametric model average prediction in panel data analysis (Q4634445) (← links)
• Error Variance Estimation in Ultrahigh-Dimensional Additive Models (Q4690960) (← links)
• Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models (Q4904729) (← links)
• Penalized estimation of high-dimensional models under a generalized sparsity cindition (Q4921673) (← links)
• Feature screening in ultrahigh-dimensional additive Cox model (Q4960596) (← links)
• Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series (Q4962456) (← links)
• Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling (Q4975410) (← links)
• Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening (Q4975579) (← links)
• (Q4998964) (← links)
• Multiple Kernel Learningの学習理論 (Q5011460) (← links)
• Univariate measurement error selection likelihood for variable selection of additive model (Q5023864) (← links)
• Additive regression splines with total variation and non negative garrote penalties (Q5039807) (← links)
• Robust sparse functional regression model (Q5042091) (← links)
• Ultrahigh‐dimensional generalized additive model: Unified theory and methods (Q5043786) (← links)
• Improvement on LASSO-type estimator in nonparametric regression (Q5051335) (← links)
• Improved Estimation of High-dimensional Additive Models Using Subspace Learning (Q5057096) (← links)
• Spectrally Sparse Nonparametric Regression via Elastic Net Regularized Smoothers (Q5066429) (← links)
• Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression (Q5066471) (← links)
• M-estimation and model identification based on double SCAD penalization (Q5075480) (← links)
• Functional Horseshoe Priors for Subspace Shrinkage (Q5146030) (← links)
• Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model (Q5146054) (← links)
• Estimation by polynomial splines with variable selection in additive Cox models (Q5169752) (← links)
• (Q5214207) (← links)
• Partially Linear Functional Additive Models for Multivariate Functional Data (Q5229922) (← links)
• Lag selection in stochastic additive models (Q5299870) (← links)
• Refined Generalization Bounds of Gradient Learning over Reproducing Kernel Hilbert Spaces (Q5380250) (← links)
• Asymptotics for penalised splines in generalised additive models (Q5419465) (← links)
• Testing for additivity in non‐parametric regression (Q5507368) (← links)
• Irrational Exuberance: Correcting Bias in Probability Estimates (Q5881099) (← links)
• Bayesian quantile regression for partially linear additive models (Q5963735) (← links)
• A selective review of group selection in high-dimensional models (Q5965305) (← links)
• A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers (Q5965308) (← links)
• Rejoinder (Q5965588) (← links)
• Grouped variable selection with discrete optimization: computational and statistical perspectives (Q6046300) (← links)
• Binacox: automatic cut‐point detection in high‐dimensional Cox model with applications in genetics (Q6055686) (← links)
• (Q6073211) (← links)
• Selection of Effects in Cox Frailty Models by Regularization Methods (Q6079979) (← links)
• Feature selection in ultrahigh-dimensional additive models with heterogeneous frequency component functions (Q6101702) (← links)
• A reluctant additive model framework for interpretable nonlinear individualized treatment rules (Q6138648) (← links)
• Generalized martingale difference divergence: detecting conditional mean independence with applications in variable screening (Q6167038) (← links)
• Measures of Uncertainty for Shrinkage Model Selection (Q6185141) (← links)
• Sparse additive models in high dimensions with wavelets (Q6196795) (← links)
• High-dimensional local linear regression under sparsity and convex losses (Q6200896) (← links)
• Variable selection in additive models via hierarchical sparse penalty (Q6490395) (← links)
• Bayesian variable selection in generalized additive partial linear models (Q6537812) (← links)