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In the 1960s, Shiryaev developed a Bayesian theory of change-point detection in the i.i.d. case, which was generalized in the beginning of the 2000s by Tartakovsky and Veeravalli for general stochastic models assuming a certain stability of…

Statistics Theory · Mathematics 2016-07-05 Chen-Der Fuh , Alexander G. Tartakovsky

In 1960s Shiryaev developed Bayesian theory of change detection in independent and identically distributed (i.i.d.) sequences. In Shiryaev's classical setting the goal is to minimize an average detection delay under the constraint imposed…

Statistics Theory · Mathematics 2010-06-07 Alexander G. Tartakovsky

The paper addresses a sequential changepoint detection problem for a general stochastic model, assuming that the observed data may be non-i.i.d. (i.e., dependent and non-identically distributed) and the prior distribution of the change…

Statistics Theory · Mathematics 2018-07-25 Alexander G. Tartakovsky

For the classical continuous-time quickest change-point detection problem it is shown that the randomized Shiryaev-Roberts-Pollak procedure is asymptotically nearly minimax-optimal (in the sense of Pollak 1985) in the class of randomized…

Statistics Theory · Mathematics 2017-04-12 Aleksey S. Polunchenko

A weighted Shiryaev-Roberts change detection procedure is shown to approximately minimize the expected delay to detection as well as higher moments of the detection delay among all change-point detection procedures with the given low…

Statistics Theory · Mathematics 2019-09-04 Serguei Pergamenchtchikov , Alexander G. Tartakovsky

Several variations of the Shiryaev-Roberts detection procedure in the context of the simple changepoint problem are considered: starting the procedure at $R_0=0$ (the original Shiryaev-Roberts procedure), at $R_0=r$ for fixed $r>0$, and at…

Statistics Theory · Mathematics 2015-03-17 Alexander G. Tartakovsky , Moshe Pollak , Aleksey S. Polunchenko

We consider the quickest change-point detection problem in pointwise and minimax settings for general dependent data models. Two new classes of sequential detection procedures associated with the maximal "local" probability of a false alarm…

Statistics Theory · Mathematics 2016-01-18 Serguei M. Pergamenchtchikov , Alexander G. Tartakovsky

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…

Statistics Theory · Mathematics 2010-06-07 Moshe Pollak , Alexander G. Tartakovsky

Assume that there are multiple data streams (channels, sensors) and in each stream the process of interest produces generally dependent and non-identically distributed observations. When the process is in a normal mode (in-control), the…

Statistics Theory · Mathematics 2018-07-25 Alexander Tartakovsky

The paper addresses a joint sequential changepoint detection and identification/isolation problem for a general stochastic model, assuming that the observed data may be dependent and non-identically distributed, the prior distribution of…

Statistics Theory · Mathematics 2021-03-04 Alexander G. Tartakovsky

Let \xi_0,\xi_1,...,\xi_{\omega-1} be observations from the hidden Markov model with probability distribution P^{\theta_0}, and let \xi_{\omega},\xi_{\omega+1},... be observations from the hidden Markov model with probability distribution…

Statistics Theory · Mathematics 2007-06-13 Cheng-Der Fuh

We address the sequential change-point detection problem for the Gaussian model where baseline distribution is Gaussian with variance \sigma^2 and mean \mu such that \sigma^2=a\mu, where a>0 is a known constant; the change is in \mu from…

Statistics Theory · Mathematics 2012-03-06 Aleksey S. Polunchenko , Alexander G. Tartakovsky , Nitis Mukhopadhyay

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-vs.-"false-positive"-risk…

Computation · Statistics 2015-04-21 Wenyu Du , Aleksey S. Polunchenko , Grigory Sokolov

For the most popular sequential change detection rules such as CUSUM, EWMA, and the Shiryaev-Roberts test, we develop integral equations and a concise numerical method to compute a number of performance metrics, including average detection…

Computation · Statistics 2011-09-15 George V. Moustakides , Aleksey S. Polunchenko , Alexander G. Tartakovsky

This paper investigates change point detection in state space models, in which the pre-change distribution $f^{\theta_0}$ is given, while the poster distribution $f^{\theta}$ after change is unknown. The problem is to raise an alarm as soon…

Probability · Mathematics 2019-06-11 Cheng-Der Fuh

We consider the problem of efficient on-line anomaly detection in computer network traffic. The problem is approached statistically, as that of sequential (quickest) changepoint detection. A multi-cyclic setting of quickest change detection…

Applications · Statistics 2013-07-23 Alexander G. Tartakovsky , Aleksey S. Polunchenko , Grigory Sokolov

We consider a unified framework of sequential change-point detection and hypothesis testing modeled by means of hidden Markov chains. One observes a sequence of random variables whose distributions are functionals of a hidden Markov chain.…

Optimization and Control · Mathematics 2013-12-13 Savas Dayanik , Kazutoshi Yamazaki

Quickest change point detection is concerned with the detection of statistical change(s) in sequences while minimizing the detection delay subject to false alarm constraints. In this paper, the problem of change point detection is studied…

Information Theory · Computer Science 2015-06-19 George Atia

In 1985, for detecting a change in distribution, Pollak introduced a specific minimax performance metric and a randomized version of the Shiryaev-Roberts procedure where the zero initial condition is replaced by a random variable sampled…

Statistics Theory · Mathematics 2015-03-13 Aleksey S. Polunchenko , Alexander G. Tartakovsky

A new class of stochastic processes called independent and periodically identically distributed (i.p.i.d.) processes is defined to capture periodically varying statistical behavior. A novel Bayesian theory is developed for detecting a…

Signal Processing · Electrical Eng. & Systems 2019-04-09 Taposh Banerjee , Prudhvi Gurram , Gene Whipps
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