The following pages link to (Q3405560):
Displaying 27 items.
- Variable selection and prediction with incomplete high-dimensional data (Q288607) (← links)
- Latent variable selection in structural equation models (Q321933) (← links)
- Dimension reduction based linear surrogate variable approach for model free variable selection (Q900762) (← links)
- A penalized likelihood method for structural equation modeling (Q1695631) (← links)
- Feature screening in ultrahigh-dimensional partially linear models with missing responses at random (Q1727907) (← links)
- Feature screening for ultrahigh dimensional categorical data with covariates missing at random (Q2008118) (← links)
- A nonparametric feature screening method for ultrahigh-dimensional missing response (Q2008122) (← links)
- Sure independence screening in the presence of missing data (Q2066525) (← links)
- Variable selection techniques after multiple imputation in high-dimensional data (Q2220289) (← links)
- Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case (Q2318820) (← links)
- Variable selection in a partial linear model with covariate data missing at random (Q2927459) (← links)
- (Q3109265) (← links)
- Simultaneous variable selection for joint models of longitudinal and survival outcomes (Q3465745) (← links)
- Variable selection when missing values are present: a case study (Q4924360) (← links)
- Variable selection for longitudinal data with high-dimensional covariates and dropouts (Q4960570) (← links)
- Bayesian adaptive Lasso for quantile regression models with nonignorably missing response data (Q5087547) (← links)
- Variable selection for high‐dimensional generalized linear model with block‐missing data (Q6049794) (← links)
- Simultaneous variable selection and estimation for joint models of longitudinal and failure time data with interval censoring (Q6055538) (← links)
- Penalized Regression for Multiple Types of Many Features With Missing Data (Q6086158) (← links)
- Spatio‐temporal Bayesian model selection for disease mapping (Q6179754) (← links)
- Covariate selection for multilevel models with missing data (Q6540496) (← links)
- A unified framework of analyzing missing data and variable selection using regularized likelihood (Q6561261) (← links)
- Variable selection for high-dimensional incomplete data using horseshoe estimation with data augmentation (Q6571743) (← links)
- Variable selection in the presence of missing data: imputation-based methods (Q6607056) (← links)
- A modified Nadaraya–Watson procedure for variable selection and nonparametric prediction with missing data (Q6611238) (← links)
- Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping (Q6625881) (← links)
- Statistical inference for high-dimensional linear regression with blockwise missing data (Q6671926) (← links)
