ON OPTIMALITY PROPERTIES OF THE SHIRYAEV-ROBERTS PROCEDURE

By Moshe Pollak, Alexander G. Tartakovsky. 2007

106 citations recorded by the source corpus.

We consider the simple changepoint problem setting, where observations are independent, iid pre-change and iid post-change, with known pre- and post-change distributions. The Shiryaev-Roberts detection procedure is known to be asymptotically minimax in the sense of minimizing maximal expected detection delay subject to a bound on the average run length to false alarm, as the latter goes to infinity. Here we present other optimality properties of the Shiryaev-Roberts procedure.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/96b9e40fb9d76e1cb3380dacc17dec33382c2caa

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In Statistics and Probability

Citations in the corpus

On optimality of the Shiryaev-Roberts procedure for detecting a change in distribution (2009, methodology): “…then it minimizes the integral average detection delay I(T ) = ∑∞ ν=0 Eν(T − ν)+ E∞T over all stopping times T that satisfy (3) E∞T > γ, where γ > 1 is a value set before the surveillance begins (cf. Pollak and Tartakovsky, 2009 and also Feinberg and Shiryaev, 2006 for the Brownian motion model).”
Numerical Comparison of CUSUM and Shiryaev–Roberts Procedures for Detecting Changes in Distributions (2009, background): “of y. On the other hand, it follows from Pollak and Tartakovsky (2009) that the Shiryaev–Roberts procedure is optimal with respect to the relative integral average detection delay measure”
Data-efficient minimax quickest change detection (2012, methodology): “Further, in [22], the SR algorithm is shown to be exactly optimal with respect to a number of other interesting criteria.”