Pages that link to "Item:Q288607"
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The following pages link to Variable selection and prediction with incomplete high-dimensional data (Q288607):
Displaying 15 items.
- Sure independence screening in the presence of missing data (Q2066525) (← links)
- Variable selection techniques after multiple imputation in high-dimensional data (Q2220289) (← links)
- Logistic regression with missing covariates -- parameter estimation, model selection and prediction within a joint-modeling framework (Q2305304) (← links)
- Bayesian additive regression trees in spatial data analysis with sparse observations (Q5040537) (← links)
- An ensemble learning method for variable selection: application to high-dimensional data and missing values (Q5055250) (← links)
- Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods (Q5057238) (← links)
- Adaptive Bayesian SLOPE: Model Selection With Incomplete Data (Q5083360) (← links)
- Integrating Multisource Block-Wise Missing Data in Model Selection (Q5881971) (← links)
- Penalized estimating equations for generalized linear models with multiple imputation (Q6179132) (← links)
- Adjusted feature screening for ultra-high dimensional missing response (Q6552579) (← links)
- Variable selection for high-dimensional incomplete data (Q6554244) (← links)
- Variable selection for high-dimensional incomplete data using horseshoe estimation with data augmentation (Q6571743) (← links)
- High-dimensional missing data imputation via undirected graphical model (Q6606959) (← links)
- Variable selection in the presence of missing data: imputation-based methods (Q6607056) (← links)
- A modified Nadaraya–Watson procedure for variable selection and nonparametric prediction with missing data (Q6611238) (← links)
