Pages that link to "Item:Q5109912"

The following pages link to Imputed Factor Regression for High-dimensional Block-wise Missing Data (Q5109912):

Displaying 11 items.

• Mallows model averaging with effective model size in fragmentary data prediction (Q2143019) (← 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)
• Integrating Multisource Block-Wise Missing Data in Model Selection (Q5881971) (← links)
• Weighted multiple blockwise imputation method for high-dimensional regression with blockwise missing data (Q5887986) (← links)
• Multinomial logistic factor regression for multi-source functional block-wise missing data (Q6057049) (← links)
• Integrative Factor Regression and Its Inference for Multimodal Data Analysis (Q6110734) (← links)
• Prediction approaches for partly missing multi-omics covariate data: a literature review and an empirical comparison study (Q6604324) (← links)
• Bayesian sensitivity analyses for longitudinal data with dropouts that are potentially missing not at random: a high dimensional pattern-mixture model (Q6627957) (← links)
• Jackknife model averaging for linear regression models with missing responses (Q6643291) (← links)
• Factor-adjusted tests for generalized linear models with multimodal data: an application to breast cancer data (Q6668586) (← links)