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Reflections on the Foundations of Probability and Statistics

Essays in Honor of Teddy Seidenfeld

  • Brings together quality scholarship

  • Examines findings in imprecise probability

  • Contains unique state-of-the-art research

Part of the book series: Theory and Decision Library A: (TDLA, volume 54)

Buying options

Hardcover Book USD 139.99
Price excludes VAT (USA)
This title has not yet been released. You will be able to pre-order it soon.

About this book

This festschrift for Teddy Seidenfeld is a collection of newly commissioned essays on the foundations of probability and statistics by leading experts in the field.  Each contribution touches on Teddy’s seminal contributions and gives an up-to-date state of the field that cannot be found elsewhere. The title, “a reflection on the foundations of probability and statistics”, which calls back to Teddy’s groundbreaking book (with Kadane and Schervish), “Rethinking the Foundations of Probability and Statistics”, bookends a career that has made fundamental contributions to a deeper understanding of uncertainty. It is aimed at all scholars engaged in probability and statistics.

Keywords

  • Imprecise Probability
  • Foundations of Probability
  • Foundations of Statistics
  • Teddy Seidenfeld
  • Bayesian Theory

Editors and Affiliations

  • Department of Statistics, Ludwig-Maximilians-University of Munich, Munich, Germany

    Thomas Augustin

  • Cidade Universitaria, Brazilian Computer Society, Sao Paulo, Brazil

    Fabio Gagliardi Cozman

  • Frankfurt School of Finance & Management, Frankfurt am Main, Germany

    Gregory Wheeler

About the editors

Thomas Augustin is Professor of Statistics at Ludwig-Maximilians-Universität München (LMU Munich), where he heads the "Foundations of Statistics and their Applications" Lab. His research interest is to develop set-valued methods for reliable statistical inference, decision making, and machine learning. For this, he utilizes
concepts from imprecise probabilities and partial identification to cope with different kinds of complex uncertainty, like non-randomly missing or coarsened data, non-standard measurement error, ambiguity,
conflicting information, and structural model indeterminacy. 

Fabio G. Cozman is Professor of Computer Science at Escola Politécnica, Universidade de São Paulo (USP), Director of the Center for Artificial Intelligence at USP, with an interest in machine learning and knowledge/uncertainty representation. Engineer (USP) and PhD (Carnegie Mellon University, USA), he has served as Program and General Chair of the Conference on Uncertainty in Artificial Intelligence, Area Chair of the International Joint Conference on Artificial Intelligence, and Associate Editor of the Artificial Intelligence Journal, the Journal of Artificial Intelligence Research, and the Journal of Approximate Reasoning.

Gregory Wheeler is Professor of Philosophy and Computer Science at Frankfurt School of Finance & Management, where he heads the Center for Human & Machine Intelligence and is Academic Director of the Master of Applied Data Science program.  His research interests concern the foundations of probability, bounded rationality, and decision-making under uncertainty involving underspecified models, conflicting information, computational resource bounds, and indeterminacy.  He also co-founded Exaloan AG, a Frankfurt-based financial services software company, where he is Head of Machine Learning.


Bibliographic Information

Buying options

Hardcover Book USD 139.99
Price excludes VAT (USA)
This title has not yet been released. You will be able to pre-order it soon.