Pages that link to "Item:Q1926385"
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The following pages link to Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces (Q1926385):
Displaying 16 items.
- Semiparametric Bayesian information criterion for model selection in ultra-high dimensional additive models (Q391941) (← links)
- Variable selection in high-dimensional sparse multiresponse linear regression models (Q779699) (← links)
- Edge detection in sparse Gaussian graphical models (Q1615220) (← links)
- Banded spatio-temporal autoregressions (Q1739642) (← links)
- High-dimensional variable selection via low-dimensional adaptive learning (Q2044323) (← links)
- Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals (Q2062391) (← links)
- Extended Bayesian information criterion in the Cox model with a high-dimensional feature space (Q2352446) (← links)
- Extended BIC for small-\(n\)-large-\(P\) sparse GLM (Q2883899) (← links)
- Extended Bayesian information criteria for model selection with large model spaces (Q3181918) (← links)
- A High‐dimensional Focused Information Criterion (Q4637090) (← links)
- Sequential Lasso Cum EBIC for Feature Selection With Ultra-High Dimensional Feature Space (Q4975573) (← links)
- Consistency of BIC Model Averaging (Q5067439) (← links)
- A Structural‐Factor Approach to Modeling High‐Dimensional Time Series and Space‐Time Data (Q5377201) (← links)
- The EBIC and a sequential procedure for feature selection in interactive linear models with high-dimensional data (Q5963707) (← links)
- A model-based multithreshold method for subgroup identification (Q6627149) (← links)
- Uncertainty Quantification for High-Dimensional Sparse Nonparametric Additive Models (Q6636572) (← links)
