Geometric Shrinkage Priors for Kählerian Signal Filters†
AbstractWe construct geometric shrinkage priors for Kählerian signal filters. Based on the characteristics of Kähler manifolds, an efficient and robust algorithm for finding superharmonic priors which outperform the Jeffreys prior is introduced. Several ansätze for the Bayesian predictive priors are also suggested. In particular, the ansätze related to Kähler potential are geometrically intrinsic priors to the information manifold of which the geometry is derived from the potential. The implication of the algorithm to time series models is also provided. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Choi, J.; Mullhaupt, A.P. Geometric Shrinkage Priors for Kählerian Signal Filters. Entropy 2015, 17, 1347-1357.
Choi J, Mullhaupt AP. Geometric Shrinkage Priors for Kählerian Signal Filters. Entropy. 2015; 17(3):1347-1357.Chicago/Turabian Style
Choi, Jaehyung; Mullhaupt, Andrew P. 2015. "Geometric Shrinkage Priors for Kählerian Signal Filters." Entropy 17, no. 3: 1347-1357.