Abstract
Multiplier methods are used to round probabilities on finitely many categories to rational proportions. Focusing on the classical methods of Adams and Jefferson, we investigate goodness-of-fit criteria for this rounding process. Assuming that the given probabilities are uniformly distributed, we derive the limiting laws of the criteria, first when the rounding accuracy increases, and then when the number of categories grows large.
Original language | English (US) |
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Pages (from-to) | 191-207 |
Number of pages | 17 |
Journal | Metrika |
Volume | 64 |
Issue number | 2 |
DOIs | |
State | Published - Oct 2006 |
Externally published | Yes |
Keywords
- Apportionment method
- Convergence in distribution
- Gaussian limit law
- Rounding error analysis
- Sainte-Laguë divergence
- q-Stationary multiplier method
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty