Pages that link to "Item:Q2905104"
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The following pages link to Regularization and model selection with categorial effect modifiers (Q2905104):
Displaying 17 items.
- Delete or merge regressors for linear model selection (Q78545) (← links)
- Tree-structured modelling of varying coefficients (Q113880) (← links)
- Factor-Adjusted Regularized Model Selection (Q150847) (← links)
- Regularization and model selection for quantile varying coefficient model with categorical effect modifiers (Q1623652) (← links)
- Bayesian effect fusion for categorical predictors (Q1738136) (← links)
- Regularized classification for mixed continuous and categorical variables under across-location heteroscedasticity (Q1776875) (← links)
- Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model (Q2228282) (← links)
- Lasso-type penalization in the framework of generalized additive models for location, scale and shape (Q2337322) (← links)
- A uniform framework for the combination of penalties in generalized structured models (Q2418291) (← links)
- On the robustness of the generalized fused Lasso to prior specifications (Q2631367) (← links)
- Regularization and model selection with categorical predictors and effect modifiers in generalized linear models (Q4970985) (← links)
- Effect Selection and Regularization in Structured Additive Distributional Regression (Q5079616) (← links)
- Sparse group variable selection based on quantile hierarchical Lasso (Q5128673) (← links)
- Regression modelling on stratified data with the lasso (Q5384445) (← links)
- svReg: Structural varying‐coefficient regression to differentiate how regional brain atrophy affects motor impairment for Huntington disease severity groups (Q6091669) (← links)
- Variable selection in generalized functional linear models (Q6537841) (← links)
- Structure estimation of binary graphical models on stratified data: application to the description of injury tables for victims of road accidents (Q6627153) (← links)
