Pages that link to "Item:Q2066516"
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The following pages link to Nonnegative estimation and variable selection under minimax concave penalty for sparse high-dimensional linear regression models (Q2066516):
Displaying 13 items.
- Nearly unbiased variable selection under minimax concave penalty (Q117379) (← links)
- Nonnegative adaptive Lasso for ultra-high dimensional regression models and a two-stage method applied in financial modeling (Q274029) (← links)
- Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization (Q391843) (← links)
- Nonnegative-Lasso and application in index tracking (Q1615217) (← links)
- An alternating direction method of multipliers for MCP-penalized regression with high-dimensional data (Q1633879) (← links)
- Penalized and constrained LAD estimation in fixed and high dimension (Q2122803) (← links)
- Sparse estimation via lower-order penalty optimization methods in high-dimensional linear regression (Q2687439) (← links)
- Efficient sparse portfolios based on composite quantile regression for high-dimensional index tracking (Q5107785) (← links)
- Variable selection for sparse high-dimensional nonlinear regression models by combining nonnegative garrote and sure independence screening (Q5248920) (← links)
- Combination of nonconvex penalties and ridge regression for high-dimensional linear models (Q5257259) (← links)
- Time-weighted nonnegative bridge index-tracking model and its application (Q6544225) (← links)
- Nonnegative group bridge and application in financial index tracking (Q6549164) (← links)
- Robust portfolio selection for sparse index tracking under no short-selling and full investment constraints (Q6591682) (← links)
