Abstract
The probabilistic distance clustering method of works well if the cluster sizes are approximately equal. We modify that method to deal with clusters of arbitrary size and for problems where the cluster sizes are themselves unknowns that need to be estimated. In the latter case, our method is a viable alternative to the estimating multinomial (EM) method.
Original language | English (US) |
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Pages (from-to) | 603-621 |
Number of pages | 19 |
Journal | Probability in the Engineering and Informational Sciences |
Volume | 22 |
Issue number | 4 |
DOIs | |
State | Published - Oct 2008 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Management Science and Operations Research
- Industrial and Manufacturing Engineering