7 papers · 1 filter
Estimating Climate Sensitivity Using Bayesian Model Averaging for CMIP Models
Jitong Jiang, Skylar Shi, Adrian E. Raftery
The Transient Climate Response to cumulative CO2 Emissions (TCRE) is a key metric for linking greenhouse gas emissions to global temperature change and informing climate policy. Ho…
Simulation-consistent Estimation of the Marginal Likelihood for Block Models
Martin Metodiev, Marie Perrot-Dockès, Guilhem Fouetillou +2
We propose a methodology for computing marginal likelihoods for block models. The proposed estimator computes the marginal likelihood from Markov chain Monte Carlo (MCMC) samples a…
Comparing Variable Selection and Model Averaging Methods for Logistic Regression
Nikola Sekulovski, František Bartoš, Don van den Bergh +6
Model uncertainty is a central challenge in statistical models for binary outcomes such as logistic regression, arising when it is unclear which predictors should be included in th…
Reversible Jump MCMC With No Regrets: Bayesian Variable Selection Using Mixtures of Mutually Singular Distributions
Don van den Bergh, Merlise A. Clyde, Adrian E. Raftery +1
Bayesian variable selection requires sampling from a posterior distribution that combines discrete model indicators with continuously varying parameters, a challenge often addresse…
Easily Computed Marginal Likelihoods for Multivariate Mixture Models Using the THAMES Estimator
Martin Metodiev, Nicholas J. Irons, Marie Perrot-Dockès +2
We present a new version of the truncated harmonic mean estimator (THAMES) for univariate or multivariate mixture models. The estimator computes the marginal likelihood from Markov…
Multiple Imputation of Hierarchical Nonlinear Time Series Data with an Application to School Enrollment Data
Daphne H. Liu, Adrian E. Raftery
International comparisons of hierarchical time series data sets based on survey data, such as annual country-level estimates of school enrollment rates, can suffer from large amoun…