854 research outputs found
Marginalization using the metric of the likelihood
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 singularities in the expectation value integral of these
parameters, especially if the prior information is not sufficient to take care
of finite integral values. However, the problem may be solved by obeying the
correct Riemannian metric imposed by the likelihood. This will be demonstrated
for the example of the electron temperature evaluation in hydrogen plasmas.Comment: 8 pages, 2 figures, Presented at the MaxEnt 2000 conference in
Gif-sur-Yvette/Pari
Bayesian analysis of magnetic island dynamics
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 equation are obtained by employing Bayesian probability
theory. Additionally a typical Bayesian change point is solved in the process
of obtaining the data.Comment: 10 pages, 4 figures, submitted to be included in MaxEnt 2002
proceeding
Decomposition of multicomponent mass spectra using Bayesian probability theory
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 applies also to the analysis of spectra containing
unstable species. For the example of mixtures of three different hydrocarbon
gases the algorithm provides concentrations and cracking coefficients of each
mixture component as well as their confidence intervals. The amount of
information needed to obtain reliable results and its relation to the accuracy
of our analysis are discussed
Norway spruce (Picea abies): Bayesian analysis of the relationship between temperature and bud burst
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