p-values for model evaluation
Abstract
Deciding whether a model provides a good description of data is often based on a goodness-of-fit criterion summarized by a p-value. Although there is considerable confusion concerning the meaning of p-values, leading to their misuse, they are nevertheless of practical importance in common data analysis tasks. We motivate their application using a Bayesian argumentation. We then describe commonly and less commonly known discrepancy variables and how they are used to define p-values. The distribution of these are then extracted for examples modeled on typical data analysis tasks, and comments on their usefulness for determining goodness-of-fit are given.
- Publication:
-
Physical Review D
- Pub Date:
- January 2011
- DOI:
- 10.1103/PhysRevD.83.012004
- arXiv:
- arXiv:1011.1674
- Bibcode:
- 2011PhRvD..83a2004B
- Keywords:
-
- 02.50.-r;
- Probability theory stochastic processes and statistics;
- Physics - Data Analysis;
- Statistics and Probability
- E-Print:
- 33 pages, 13 figures