Abstract
Adjusting a drifting process to minimize the expected sum of quadratic off-target and fixed adjustment costs is considered under unknown process parameters. A Bayesian approach based on sequential Monte Carlo methods is presented. The benefits of the resulting "deadband" adjustment policy are studied.
Original language | English (US) |
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Pages (from-to) | 843-852 |
Number of pages | 10 |
Journal | Statistics and Probability Letters |
Volume | 77 |
Issue number | 8 |
DOIs | |
State | Published - Apr 15 2007 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty