Pages that link to "Item:Q2864067"
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The following pages link to Univariate shrinkage in the Cox model for high dimensional data (Q2864067):
Displaying 25 items.
- Enhancing the lasso approach for developing a survival prediction model based on gene expression data (Q308770) (← links)
- High-dimensional Cox regression analysis in genetic studies with censored survival outcomes (Q454771) (← links)
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates (Q764508) (← links)
- A Bayesian hybrid huberized support vector machine and its applications in high-dimensional medical data (Q901503) (← links)
- Censored cumulative residual independent screening for ultrahigh-dimensional survival data (Q1642144) (← links)
- Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review (Q1650703) (← links)
- Variable selection for high-dimensional genomic data with censored outcomes using group Lasso prior (Q1654247) (← links)
- A new nonparametric screening method for ultrahigh-dimensional survival data (Q1662088) (← links)
- Majorization-minimization algorithms for nonsmoothly penalized objective functions (Q1952099) (← links)
- Model-free feature screening for high-dimensional survival data (Q1989891) (← links)
- Model-free feature screening via distance correlation for ultrahigh dimensional survival data (Q2062408) (← links)
- Conditional screening for ultrahigh-dimensional survival data in case-cohort studies (Q2074082) (← links)
- Variable screening for varying coefficient models with ultrahigh-dimensional survival data (Q2143009) (← links)
- Bayesian shrinkage methods for partially observed data with many predictors (Q2441860) (← links)
- High-dimensional Cox models: the choice of penalty as part of the model building process (Q2786152) (← links)
- Predicting Patient Survival from Proteomic Profile using Mass Spectrometry Data: An Empirical Study (Q4921574) (← links)
- Survival prediction and variable selection with simultaneous shrinkage and grouping priors (Q4969996) (← links)
- The Lq-norm learning for ultrahigh-dimensional survival data: an integrative framework (Q5134474) (← links)
- Model-free slice screening for ultrahigh-dimensional survival data (Q5861483) (← links)
- Binacox: automatic cut‐point detection in high‐dimensional Cox model with applications in genetics (Q6055686) (← links)
- Volume under the ROC surface for high-dimensional independent screening with ordinal competing risk outcomes (Q6092303) (← links)
- A New Model-Free Feature Screening Procedure for Ultrahigh-Dimensional Interval-Censored Failure Time Data (Q6092947) (← links)
- Model‐free conditional screening for ultrahigh‐dimensional survival data via conditional distance correlation (Q6141306) (← links)
- Variable selection for censored data using modified correlation adjusted correlation (MCAR) scores (Q6628007) (← links)
- Penalized weighted proportional hazards model for robust variable selection and outlier detection (Q6628641) (← links)
