Pages that link to "Item:Q5881971"
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The following pages link to Integrating Multisource Block-Wise Missing Data in Model Selection (Q5881971):
Displaying 13 items.
- Mallows model averaging with effective model size in fragmentary data prediction (Q2143019) (← links)
- Imputation for multisource data with comparison and assessment techniques (Q4620238) (← links)
- Imputed Factor Regression for High-dimensional Block-wise Missing Data (Q5109912) (← links)
- Optimal Sparse Linear Prediction for Block-missing Multi-modality Data Without Imputation (Q5120677) (← links)
- Model averaging for generalized linear models in fragmentary data prediction (Q5880143) (← links)
- Weighted multiple blockwise imputation method for high-dimensional regression with blockwise missing data (Q5887986) (← links)
- Variable selection for high‐dimensional generalized linear model with block‐missing data (Q6049794) (← links)
- Multinomial logistic factor regression for multi-source functional block-wise missing data (Q6057049) (← links)
- Penalized estimating equations for generalized linear models with multiple imputation (Q6179132) (← links)
- Regularized Buckley-James method for right-censored outcomes with block-missing multimodal covariates (Q6544014) (← links)
- Prediction approaches for partly missing multi-omics covariate data: a literature review and an empirical comparison study (Q6604324) (← links)
- Jackknife model averaging for linear regression models with missing responses (Q6643291) (← links)
- Statistical inference for high-dimensional linear regression with blockwise missing data (Q6671926) (← links)
