Pages that link to "Item:Q480967"

The following pages link to Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data (Q480967):

Displaying 36 items.

• Local linear smoothing for sparse high dimensional varying coefficient models (Q276223) (← links)
• A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model (Q830540) (← links)
• Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models (Q892254) (← links)
• Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients (Q1615281) (← links)
• Feature screening for generalized varying coefficient models with application to dichotomous responses (Q1659028) (← links)
• Feature screening in ultrahigh-dimensional partially linear models with missing responses at random (Q1727907) (← links)
• Variable screening for high dimensional time series (Q1746535) (← links)
• A note on quantile feature screening via distance correlation (Q2010823) (← links)
• The de-biased group Lasso estimation for varying coefficient models (Q2046473) (← links)
• Penalized kernel quantile regression for varying coefficient models (Q2059422) (← links)
• A double varying-coefficient modeling approach for analyzing longitudinal observations (Q2274194) (← links)
• Screening and selection for quantile regression using an alternative measure of variable importance (Q2274955) (← links)
• Sure independence screening in ultrahigh dimensional generalized additive models (Q2317245) (← links)
• Adaptively weighted group Lasso for semiparametric quantile regression models (Q2325373) (← links)
• Semiparametric partially linear varying coefficient models with panel count data (Q2364044) (← links)
• Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data (Q2418503) (← links)
• Nonparametric independence screening for ultra-high-dimensional longitudinal data under additive models (Q4559457) (← links)
• Semiparametric model average prediction in panel data analysis (Q4634445) (← links)
• Greedy forward regression for variable screening (Q4639813) (← links)
• Model Selection for High-Dimensional Quadratic Regression via Regularization (Q4962427) (← links)
• Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series (Q4962456) (← links)
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models (Q4975577) (← links)
• Copula-based Partial Correlation Screening: a Joint and Robust Approach (Q4986377) (← links)
• Feature screening of quadratic inference functions for ultrahigh dimensional longitudinal data (Q5036899) (← links)
• Conditional sparse boosting for high-dimensional instrumental variable estimation (Q5040523) (← links)
• Modified adaptive group lasso for high-dimensional varying coefficient models (Q5055141) (← links)
• Sparsity identification in ultra-high dimensional quantile regression models with longitudinal data (Q5077985) (← links)
• Optimal model averaging estimation for correlation structure in generalized estimating equations (Q5085950) (← links)
• Structural identification and variable selection in high-dimensional varying-coefficient models (Q5266564) (← links)
• Ultra high‐dimensional semiparametric longitudinal data analysis (Q6076502) (← links)
• Feature Screening with Latent Responses (Q6079779) (← links)
• RaSE: A Variable Screening Framework via Random Subspace Ensembles (Q6107221) (← links)
• Forward selection for feature screening and structure identification in varying coefficient models (Q6133729) (← links)
• Simultaneous selection and inference for varying coefficients with zero regions: a soft-thresholding approach (Q6589282) (← links)
• Improvement screening for ultra-high dimensional data with censored survival outcomes and varying coefficients (Q6636148) (← links)
• Model-averaging-based semiparametric modeling for conditional quantile prediction (Q6649847) (← links)