Pages that link to "Item:Q2809556"
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The following pages link to A permutation approach for selecting the penalty parameter in penalized model selection (Q2809556):
Displaying 11 items.
- Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models (Q2134161) (← links)
- Prediction error bounds for linear regression with the TREX (Q2273161) (← links)
- Tuning parameter calibration for \(\ell_1\)-regularized logistic regression (Q2317308) (← links)
- An m-estimation-based model selection criterion with a data-oriented penalty (Q2774411) (← links)
- Shrinkage parameter selection via modified cross-validation approach for ridge regression model (Q5086327) (← links)
- A Tuning-free Robust and Efficient Approach to High-dimensional Regression (Q5146020) (← links)
- Discussion of “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression” (Q5146022) (← links)
- Regularisation Parameter Selection Via Bootstrapping (Q5361202) (← links)
- Using the Penalized Likelihood Method for Model Selection with Nuisance Parameters Present only under the Alternative: An Application to Switching Regression Models (Q5467624) (← links)
- Variable selection for discrete survival model with frailty in presence of left truncation and right censoring: studying association of environmental toxicants on time-to-pregnancy (Q6629922) (← links)
- Integrating additional knowledge into the estimation of graphical models (Q6637073) (← links)
