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) |
|---|---|
| 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