Abstract
In his interesting paper Mei criticized the use of the expected run length as the mean for controlling the rate of false detection and proposed alternative measures. In this paper we join Mei's attack on the traditional constraint by claiming that the rate of detection is a local phenomena, and hence should be balanced against local constraints on false detection. We propose local probabilistic constraints on the rate of false detection and demonstrate their usefulness in the detection of a shift in a normal mean with an unknown baseline.
Original language | English |
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Pages (from-to) | 406-410 |
Number of pages | 5 |
Journal | Sequential Analysis |
Volume | 27 |
Issue number | 4 |
DOIs |
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State | Published - Oct 2008 |
Keywords
- Asymptotic optimality
- Change-point detection
- False detection rate
- Invariant statistics