333 citations · 349 across the 20 of their papers we have counts for
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stat.CO2018★ 2 cited
An Asymptotically Efficient Metropolis-Hastings Sampler for Bayesian Inference in Large-Scale Educational Measuremen
Timo Bechger, Gunter Maris, Maarten Marsman
This paper discusses a Metropolis-Hastings algorithm developed by \citeA{MarsmanIsing}. The algorithm is derived from first principles, and it is proven that the algorithm becomes…
stat.CO2017★ 1 cited
A Tutorial on Bridge Sampling
Quentin F. Gronau, Alexandra Sarafoglou, Dora Matzke +7
The marginal likelihood plays an important role in many areas of Bayesian statistics such as parameter estimation, model comparison, and model averaging. In most applications, howe…