Model uncertainty
From MaRDI portal
Publication:1766316
DOI10.1214/088342304000000035zbMath1062.62044OpenAlexW4250518393MaRDI QIDQ1766316
Edward I. George, Merlise A. Clyde
Publication date: 7 March 2005
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/088342304000000035
nonparametric regressionlinear regressionvariable selectionregression treesreversible jump Markov chain Monte Carlomodel averagingBayesian factors: classificationobjective prior distributions
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Uses Software
Cites Work
- Proper Bayes Minimax Estimators of the Multivariate Normal Mean
- Graphical models
- Simulating normalizing constants: From importance sampling to bridge sampling to path sampling
- Benchmark priors for Bayesian model averaging.
- A case study of stochastic optimization in health policy: Problem formulation and preliminary results
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- On Bayesian model and variable selection using MCMC
- Nonparametric regression using Bayesian variable selection
- Estimating the dimension of a model
- On Monte Carlo methods for estimating ratios of normalizing constants
- Bayesian model averaging: A tutorial. (with comments and a rejoinder).
- Nonparametric Bayesian data analysis
- Computational advances for and from Bayesian analysis
- Graph puzzles, homotopy, and the alternating group
- Prior elicitation for model selection and estimation in generalized linear mixed models
- Variable selection in qualitative models via an entropic explanatory power
- Bayesian variable and link determination for generalised linear models
- Approximations and consistency of Bayes factors as model dimension grows
- Spline adaptation in extended linear models
- Optimal predictive model selection.
- Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
- Markov chains for exploring posterior distributions. (With discussion)
- The risk inflation criterion for multiple regression
- Monte Carlo methods in Bayesian computation
- Empirical Bayes vs. fully Bayes variable selection
- A Bayesian Approach to Selecting Covariates for Prediction
- Calibration and empirical Bayes variable selection
- Efficient estimation of covariance selection models
- The Intrinsic Bayes Factor for Model Selection and Prediction
- Marginal Likelihood from the Gibbs Output
- Sampling-Based Approaches to Calculating Marginal Densities
- Accurate Approximations for Posterior Moments and Marginal Densities
- Bayesian Variable Selection in Linear Regression
- Approximate Bayes factors and accounting for model uncertainty in generalised linear models
- A Bayesian Approach to Robust Binary Nonparametric Regression
- Model choice: a minimum posterior predictive loss approach
- The Schwarz criterion and related methods for normal linear models
- Regression Selection Strategies and Revealed Priors
- A Bayesian CART algorithm
- Multiple shrinkage and subset selection in wavelets
- Automatic Bayesian Curve Fitting
- Wavelet Thresholding via A Bayesian Approach
- Multivariate Bayesian Variable Selection and Prediction
- Bayesian Inference on Network Traffic Using Link Count Data
- Prior Elicitation, Variable Selection and Bayesian Computation for Logistic Regression Models
- Importance-Weighted Marginal Bayesian Posterior Density Estimation
- Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
- The Bayesian Modeling of Covariates for Population Pharmacokinetic Models
- Prediction Via Orthogonalized Model Mixing
- Bayesian Model Averaging for Linear Regression Models
- Computing Bayes Factors by Combining Simulation and Asymptotic Approximations
- Estimating Bayes Factors via Posterior Simulation With the Laplace-Metropolis Estimator
- Adaptive Bayesian Wavelet Shrinkage
- A Bayesian Approach to Nonparametric Bivariate Regression
- Bayesian Model Averaging in Proportional Hazard Models: Assessing the Risk of a Stroke
- Model Selection in Spline Nonparametric Regression
- Model Selection and the Principle of Minimum Description Length
- Expected-posterior prior distributions for model selection
- Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
- Parsimonious Covariance Matrix Estimation for Longitudinal Data
- Bayesian variable selection for proportional hazards models
- Flexible Empirical Bayes Estimation for Wavelets
- Stochastic search variable selection for log-linear models
- Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior
- Bayes Factors and Approximations for Variance Component Models
- The Variable Selection Problem
- Bayes Model Averaging with Selection of Regressors
- Efficient Construction of Reversible Jump Markov Chain Monte Carlo Proposal Distributions
- Marginal Likelihood From the Metropolis–Hastings Output
- Bayesian Variable Selection and Regularization for Time–Frequency Surface Estimation
- Computing Bayes Factors Using a Generalization of the Savage-Dickey Density Ratio
- Bayes Factors
- Bayesian Graphical Models for Discrete Data
- Bayesian variable selection with related predictors
- Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
- The choice of variables in multivariate regression: a non-conjugate Bayesian decision theory approach
- Decomposable graphical Gaussian model determination
- A Monte Carlo method for computing the marginal likelihood in nondecomposable Gaussian graphical models