357 citations · 901 across the 11 of their papers we have counts for
5 papers · 1 filter
Entropic Priors
Ariel Caticha, Roland Preuss
The method of Maximum (relative) Entropy (ME) is used to translate the information contained in the known form of the likelihood into a prior distribution for Bayesian inference. T…
Maximum Entropy and Bayesian Data Analysis: Entropic Priors
Ariel Caticha, Roland Preuss
The problem of assigning probability distributions which objectively reflect the prior information available about experiments is one of the major stumbling blocks in the use of Ba…
Bayesian analysis of magnetic island dynamics
R. Preuss, M. Maraschek, H. Zohm +1
We examine a first order differential equation with respect to time coming up in the description of magnetic islands in magnetically confined plasmas. The free parameters of this e…
Marginalization using the metric of the likelihood
R. Preuss, V. Dose
Although the likelihood function is normalizeable with respect to the data there is no guarantee that the same holds with respect to the model parameters. This may lead to singular…
Decomposition of multicomponent mass spectra using Bayesian probability theory
H. D. Kang, R. Preuss, T. Schwarz-Selinger +1
We present a method for the decomposition of mass spectra of mixture gases using Bayesian probability theory. The method works without any calibration measurement and therefore app…