Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model

Frank P. A. Coolen, Thomas Augustin. Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model. In Fabio Gagliardi Cozman, Robert Nau, Teddy Seidenfeld, editors, ISIPTA 05, Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications, Carnegie Mellon University, Pittsburgh, PA, USA, July 20-23 2005. pages 125-134, SIPTA, 2005.

@inproceedings{CoolenA05,
  title = {Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model},
  author = {Frank P. A. Coolen and Thomas Augustin},
  year = {2005},
  tags = {data-flow},
  researchr = {https://researchr.org/publication/CoolenA05},
  cites = {0},
  citedby = {0},
  pages = {125-134},
  booktitle = {ISIPTA  05, Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications, Carnegie Mellon University, Pittsburgh, PA, USA, July 20-23 2005},
  editor = {Fabio Gagliardi Cozman and Robert Nau and Teddy Seidenfeld},
  publisher = {SIPTA},
}