Abstract
Observations are taken independently and sequentially. Detection of a change in distribution is studied when the problem has an invariance structure. The prechange distribution is assumed to be a member of a specified family and is assumed known up to a nuisance parameter. We provide a general method of constructing surveillance schemes in the presence of a nuisance parameter and give sufficient conditions for approximating their average run lengths to false alarm. Applications include detecting a change in scale of i.i.d. gamma variates with unknown initial scale, detecting a change in location of i.i.d. normal variates with unknown initial mean, and a non-parametric scheme based on ranks for detecting a change to a stochastically larger distribution.
| Original language | English |
|---|---|
| Pages (from-to) | 1284-1310 |
| Number of pages | 27 |
| Journal | Annals of Statistics |
| Volume | 25 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 1997 |
Keywords
- Change-point
- Cusum
- Disruption
- Invariance