On the quantification of model uncertainty: a Bayesian perspective
From MaRDI portal
Publication:823871
DOI10.1007/s11336-021-09754-5zbMath1476.62247OpenAlexW3135946712MaRDI QIDQ823871
Publication date: 16 December 2021
Published in: Psychometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11336-021-09754-5
Cites Work
- Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
- Randomization-based inference about latent variables from complex samples
- Bayesian model averaging: A tutorial. (with comments and a rejoinder).
- Using stacking to average Bayesian predictive distributions (with discussion)
- A Bayes interpretation of stacking for \(\mathcal{M}\)-complete and \(\mathcal{M}\)-open settings
- Model uncertainty
- The risk inflation criterion for multiple regression
- Stacked regressions
- Scoring rules and the evaluation of probabilities. (With discussion)
- A survey of Bayesian predictive methods for model assessment, selection and comparison
- Comparison of Bayesian predictive methods for model selection
- The Bayesian elastic net
- Calibration and empirical Bayes variable selection
- Present Position and Potential Developments: Some Personal Views: Statistical Theory: The Prequential Approach
- Scoring Rules, Generalized Entropy, and Utility Maximization
- Model Selection and Model Averaging
- Mixtures of g Priors for Bayesian Variable Selection
- The Bayesian Lasso
- Accurate Approximations for Posterior Moments and Marginal Densities
- Approximate Bayes factors and accounting for model uncertainty in generalised linear models
- The Well-Calibrated Bayesian
- Regressions by Leaps and Bounds
- A Predictive Approach to Model Selection
- Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
- Bayesian Model Averaging for Linear Regression Models
- Model Selection and the Principle of Minimum Description Length
- Frequentist Model Average Estimators
- Model Selection and Multimodel Inference
- Predictive Statistics
- Choosing a Strictly Proper Scoring Rule
- Bayes Factors
- Bayesian Graphical Models for Discrete Data
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Regularization and Variable Selection Via the Elastic Net
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- On Information and Sufficiency
- Benchmark priors for Bayesian model averaging.
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: On the quantification of model uncertainty: a Bayesian perspective
