Pages that link to "Item:Q961929"

The following pages link to Penalized factor mixture analysis for variable selection in clustered data (Q961929):

Displaying 16 items.

• Inferring food intake from multiple biomarkers using a latent variable model (Q132201) (← links)
• Using conditional independence for parsimonious model-based Gaussian clustering (Q746302) (← links)
• Penalized cluster analysis with applications to family data (Q901606) (← links)
• Model-based clustering of high-dimensional data: a review (Q1621282) (← links)
• Modelling the role of variables in model-based cluster analysis (Q1702292) (← links)
• Prediction with a flexible finite mixture-of-regressions (Q1727867) (← links)
• Variable selection methods for model-based clustering (Q1749770) (← links)
• A Lasso-penalized BIC for mixture model selection (Q2009036) (← links)
• Discriminative variable selection for clustering with the sparse Fisher-EM algorithm (Q2259731) (← links)
• Mixtures of Gaussian copula factor analyzers for clustering high dimensional data (Q2325325) (← links)
• Variable selection in model-based clustering and discriminant analysis with a regularization approach (Q2418093) (← links)
• Bayesian variable selection and model averaging in the arbitrage pricing theory model (Q2445778) (← links)
• Model-based clustering (Q2628064) (← links)
• Variable selection via the weighted group Lasso for factor analysis models (Q2856545) (← links)
• Italian contributions on some recent research topics in cluster analysis (Q5148604) (← links)
• Clustered sparse structural equation modeling for heterogeneous data (Q6187804) (← links)