A quantum framework for likelihood ratios
Abstract
The ability to calculate precise likelihood ratios is fundamental to science, from Quantum Information Theory through to Quantum State Estimation. However, there is no assumption-free statistical methodology to achieve this. For instance, in the absence of data relating to covariate overlap, the widely used Bayes’ theorem either defaults to the marginal probability driven “naive Bayes’ classifier”, or requires the use of compensatory expectation-maximization techniques. This paper takes an information-theoretic approach in developing a new statistical formula for the calculation of likelihood ratios based on the principles of quantum entanglement, and demonstrates that Bayes’ theorem is a special case of a more general quantum mechanical expression.
- Publication:
-
International Journal of Quantum Information
- Pub Date:
- 2018
- DOI:
- arXiv:
- arXiv:2412.19321
- Bibcode:
- 2018IJQI...1650002B
- Keywords:
-
- Bayes’ theorem;
- probability;
- statistics;
- inference;
- decision-making;
- Computer Science - Artificial Intelligence