AU - Gholami, Gholamhossein
TI - On the Bayesian Sequential Change-Point Detection
PT - JOURNAL ARTICLE
TA - JIRSS
JN - JIRSS
VO - 16
VI - 1
IP - 1
4099 - http://jirss.irstat.ir/article-1-381-en.html
4100 - http://jirss.irstat.ir/article-1-381-en.
SO - JIRSS 1
ABĀ - The problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. We discuss a Bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. Two cases are considered: (i) p0 and p1 are fully known, (ii) p0 and p1 belong to the same family of distributions with some unknown parameters θ1≠θ2. We present a maximum a posteriori estimate of the change-point which, for the case (i), can be computed in a sequential manner. In addition, we propose the use of the Shiryaev's loss function. Under this assumption, we define a Bayesian stopping rule. For the Poisson distribution and in the two cases (i) and (ii), we obtain results for the conjugate prior.
CP - IRAN
IN -
LG - eng
PB - JIRSS
PG - 77
PT - Original Paper
YR - 2017