Publications (8)
Approximating evidence via bounded harmonic means
Dana Naderi, Christian P Robert, Kaniav Kamary +1
Efficient Bayesian model selection relies on the model evidence or marginal likelihood, whose computation often requires evaluating an intractable integral. The harmonic mean estim…
Estimation of cosmological parameters using adaptive importance sampling
Darren Wraith, Martin Kilbinger, Karim Benabed +5
We present a Bayesian sampling algorithm called adaptive importance sampling or Population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the…
CosmoPMC: Cosmology Population Monte Carlo
Martin Kilbinger, Karim Benabed, Olivier Cappe +7
We present the public release of the Bayesian sampling algorithm for cosmology, CosmoPMC (Cosmology Population Monte Carlo). CosmoPMC explores the parameter space of various cosmol…
Computational methods for Bayesian model choice
Christian P. Robert, Darren Wraith
In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we…
Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions
Darren Wraith, Kerrie Mengersen, Clair Alston +2
The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared usi…
Clustering using skewed multivariate heavy tailed distributions with flexible tail behaviour
Darren Wraith, Florence Forbes
The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. It nests as particular cases several important asymmet…