Performance of variable and function selection methods for estimating the nonlinear health effects of correlated chemical mixtures: a simulation study
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Publication:6629851
DOI10.1002/sim.8701zbMath1546.62429MaRDI QIDQ6629851
Nina Lazarevic, Luke D. Knibbs, Peter D. Sly, Adrian G. Barnett
Publication date: 30 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
Cites Work
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- BART: Bayesian additive regression trees
- Detecting Novel Associations in Large Data Sets
- Variable selection for BART: an application to gene regulation
- Practical variable selection for generalized additive models
- On multicollinearity and concurvity in some nonlinear multivariate models
- Stabilizing the Lasso against cross-validation variability
- Penalized likelihood and Bayesian function selection in regression models
- Optimal predictive model selection.
- On the impact of model selection on predictor identification and parameter inference
- Stability Selection
- Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models
- Prediction with missing data via Bayesian Additive Regression Trees
- Multiple imputation of discrete and continuous data by fully conditional specification
- Semiparametric Regression of Multidimensional Genetic Pathway Data: Least‐Squares Kernel Machines and Linear Mixed Models
- The Elements of Statistical Learning
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