1 citations · 2 across the 7 of their papers we have counts for
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stat.CO2025
An MCMC hypothesis test to check a claimed sampler: applied to a claimed sampler for the G-Wishart distribution
Håkon Tjelmeland, Hanna Bu Kvaløy
Suppose we have a distribution of interest, with density say, and an algorithm claimed to generate samples from . Moreover, assume we have available a Me…
stat.CO2018
A multiple-try Metropolis-Hastings algorithm with tailored proposals
Xin Luo, Håkon Tjelmeland
We present a new multiple-try Metropolis-Hastings algorithm designed to be especially beneficial when a tailored proposal distribution is available. The algorithm is based on a giv…
stat.CO2015★ 1 cited
Approximations and bounds for binary Markov random fields
Haakon Michael Austad, Håkon Tjelmeland
Discrete Markov random fields form a natural class of models to represent images and spatial data sets. The use of such models is, however, hampered by a computationally intractabl…