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Partition function approach to non-Gaussian likelihoods: macrocanonical partitions and replicating Markov-chains
Maximilian Philipp Herzog, Heinrich von Campe, Rebecca Maria Kuntz +2
Monte-Carlo techniques are standard numerical tools for exploring non-Gaussian and multivariate likelihoods. Many variants of the original Metropolis-Hastings algorithm have been p…
Partition function approach to non-Gaussian likelihoods: partitions for the inference of functions and the Fisher-functional
Rebecca Maria Kuntz, Maximilian Philipp Herzog, Heinrich von Campe +2
Motivated by constraints on the dark energy equation of state from supernova-data, we propose a formalism for the Bayesian inference of functions: Starting at a functional variant…
Partition function approach to non-Gaussian likelihoods: physically motivated convergence criteria for Markov-chains
Lennart Röver, Heinrich von Campe, Maximilian Philipp Herzog +2
Non-Gaussian distributions in cosmology are commonly evaluated with Monte Carlo Markov-chain methods, as the Fisher-matrix formalism is restricted to the Gaussian case. The Metropo…