Christian Goulding

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Sequential change diagnosis is the joint problem of detection and identification of a sudden and unobservable change in the distribution of a random sequence. In this problem, the common probability law of a sequence of i.i.d. random variables suddenly changes at some disorder time to one of finitely many alternatives. This disorder time marks the start of(More)
The problem of detection and identification of an unobservable change in the distribution of a random sequence is studied via a hidden Markov model (HMM) approach. The formulation is Bayesian, on-line, discrete-time, allowing both single- and multiple- disorder cases, dealing with both independent and identically distributed (i.i.d.) and dependent(More)
This paper examines the joint problem of detection and identification of a sudden and unobservable change in the probability distribution function (pdf) of a sequence of independent and identically distributed (i.i.d.) random variables to one of finitely many alternative pdf's. The objective is quick detection of the change and accurate inference of the(More)
3766 * Edmans: London Business School, Regent’s Park, P-225, London NW1 4SA, UK, NBER, CEPR, and ECGI (e-mail: aedmans@london.edu); Goldstein: The Wharton School, 2321 Steinberg Hall–Dietrich Hall, 3620 Locust Walk, Philadelphia, PA 19104 (e-mail: itayg@wharton.upenn.edu); Jiang: Columbia Business School, 3022 Broadway, Uris Hall 803, New York, NY 10027(More)
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