A Pathway from Bayesian Statistical Analysis to Superstatistics

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

9 pages, LaTeX

Scientific paper

Superstatistics and Tsallis statistics in statistical mechanics is given an interpretation in terms of Bayesian statistical analysis. Subsequently superstatistics is extended by replacing each component of the conditional and marginal densities by Mathai's pathway model and further both components are replaced by Mathai's pathway models. This produces a wide class of mathematically and statistically interesting functions for prospective applications in statistical physics. It is pointed out that the final integral is a particular case of a general class of integrals introduced by the authors earlier. Those integrals are also connected to Kraetzel integrals in applied analysis, inverse Gaussian densities in stochastic processes, reaction rate integrals in the theory of nuclear astrophysics and Tsallis statistics in nonextensive statistical mechanics. The final results are obtained in terms of Fox's H-function. Matrix variate analogue of one significant specific case is also pointed out.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Pathway from Bayesian Statistical Analysis to Superstatistics does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Pathway from Bayesian Statistical Analysis to Superstatistics, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Pathway from Bayesian Statistical Analysis to Superstatistics will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-588276

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.