4 papers
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…
The Principle of Redundant Reflection
Martin Metodiev, Maarten Marsman, Lourens Waldorp +2
The fact that redundant information does not update a rational belief implies that rational beliefs are updated using Bayes rule. In the framework of Hild (1998a), this is true und…
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…
A Structured Estimator for large Covariance Matrices in the Presence of Pairwise and Spatial Covariates
Martin Metodiev, Marie Perrot-Dockès, Sarah Ouadah +4
We consider the problem of estimating a high-dimensional covariance matrix from a small number of observations when covariates on pairs of variables are available and the variables…