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Online detection of continuous changes in stochastic processes

Kohei Miyaguchi, Kenji Yamanishi
2017 International Journal of Data Science and Analytics  
We are concerned with detecting continuous changes in stochastic processes. In conventional studies on non-stationary stochastic processes, it is often assumed that changes occur abruptly.  ...  The contribution of this paper is as follows: We first propose a novel characterization of processes for continuous changes.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s41060-017-0045-2 dblp:journals/ijdsa/MiyaguchiY17 fatcat:cj5e7bg73bbixm2cie5tnjbu6i

Sequential Bayesian Inference for Detection and Response to Seasonal Epidemics

Michael Ludkovski, Junjing Lin
2013 Online Journal of Public Health Informatics  
To incorporate observed year-over-year variation in flu incidence cases and timing of outbreaks, we analyze a stochastic compartmental SIS model that includes seasonal forcing by a latent Markovian factor  ...  Epidemic detection then consists in identifying the presence of the environmental factor ("high" flu season), as well as estimation of the epidemic parameters, such as contact and recovery rates.  ...  Conclusions We developed a new Bayesian approach to joint inference of parameters and latent factors in continuous-time stochastic compartmental models.  ... 
doi:10.5210/ojphi.v5i1.4570 fatcat:77n63k6qofevtky2wgwergemdm

Author index volume 20

1985 Stochastic Processes and their Applications  
Sumita Nayak, S.S., Almost sure limit points of independent copies of sample (1) H., Periodic regeneration Vaman, H.J., Optimum online detection of parameter changes in two linear models Wilson, J.G.  ...  J. de Mare, Generation of random processes for fatigue testing (1)149-156 Imkeller, P., A stochastic calculus for continuous N-parameter strong martingales (1) l-40 Karr, A.F., State estimation for Cox  ... 
doi:10.1016/0304-4149(85)90225-x fatcat:pvpt6jgzlja65jufttgcgaofym

Nonlinear Model Predictive Control for Stochastic Differential Equation Systems

Niclas Laursen Brok, Henrik Madsen, John Bagterp Jørgensen
2018 IFAC-PapersOnLine  
Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time.  ...  Such systems are called continuous-discrete systems and provides a natural representation of systems evolving in continuous-time.  ...  Success of this approach depends on detectability of the augmented system.  ... 
doi:10.1016/j.ifacol.2018.11.071 fatcat:yaqnzuaahbesxlkudrywwkxddm

Limits in detecting acceleration of ice sheet mass loss due to climate variability

B. Wouters, J. L. Bamber, M. R. van den Broeke, J. T. M. Lenaerts, I. Sasgen
2013 Nature Geoscience  
Owing to the inability of current ice sheet models to incorporate all processes governing ice loss-in particular the complex dynamical changes of the marginal glaciers 7 and the forcing at marine margins-the  ...  We also find that the detection threshold of mass loss acceleration depends on record length: to detect an acceleration at an accuracy within ±10 Gt yr 2 , a period of 10 years or more of observations  ...  Acknowledgements The GRACE processing centres are acknowledged for processing and sharing the GRACE data. We thank G. A, R. Riva and P.  ... 
doi:10.1038/ngeo1874 fatcat:ng4ot6mggrapfnminxyzvanvuu

On-line detection of continuous changes in stochastic processes

Kohei Miyaguchi, Kenji Yamanishi
2015 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)  
We are concerned with detecting continuous changes in stochastic processes. In conventional studies on non-stationary stochastic processes, it is often assumed that changes occur abruptly.  ...  The contribution of this paper is as follows: We first propose a novel characterization of processes for continuous changes.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1109/dsaa.2015.7344783 dblp:conf/dsaa/MiyaguchiY15 fatcat:zdmliiadlvalnapceahyqr73vq

Adaptive MLSDE using the EM algorithm

H. Zamiri-Jafarian, S. Pasupathy
1999 IEEE Transactions on Communications  
The theory of adaptive sequence detection incorporating estimation of channel and related parameters is studied in the context of maximum-likelihood (ML) principles in a general framework based on the  ...  GMLSDE is developed into a real time detection/estimation algorithm using the online EM algorithm with coupling between estimation and detection.  ...  changes.  ... 
doi:10.1109/26.780454 fatcat:pg3nlzuk3nfh5gghbqqzza66dm

Detecting changes in real-time data: a user's guide to optimal detection

P. Johnson, J. Moriarty, G. Peskir
2017 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
For clarity of exposition we work in discrete time and provide a brief discussion of the continuous time setting, including recent developments using stochastic calculus.  ...  The real-time detection of changes in a noisily observed signal is an important problem in applied science and engineering.  ...  The authors would like to thank their industrial collaborators for valuable discussions over many years, and also the referees for insightful comments which improved the presentation of the paper.  ... 
doi:10.1098/rsta.2016.0298 pmid:29052544 pmcid:PMC5514354 fatcat:h7h7fae6onhjjjxwkodjrcuhhu

Optimal online detection of parameter changes in two linear models

H.J. Vaman
1985 Stochastic Processes and their Applications  
Bhat for several valuable suggestions in the preparation of this paper.  ...  Similar results were arrived at for detection of disorder in a Poisson process by Davis (1974) who formulated it as a stochastic filtering problem.  ...  The problem of online detection of the epoch of change, or disorder as it is sometimes called, consists of obtaining a sequential rule which minimizes a loss associated with the delay in detection.  ... 
doi:10.1016/0304-4149(85)90221-2 fatcat:ykwelx6zmngehhe6govybxa4oi

Table of Contents

2020 IEEE Transactions on Signal Processing  
Liu, (Contents Continued on Page xi) (Contents Continued from Page x) Generating Sparse Stochastic Processes Using Matched Splines . . . . . . . . . . . . . . . . . . L. Dadi, S.  ...  Pei 3500 NEWMA: A New Method for Scalable Model-Free Online Change-Point Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tsp.2020.3042287 fatcat:nh7viihaozhd7li3txtadnx5ui

Page 887 of The Journal of the Operational Research Society Vol. 58, Issue 7 [page]

2007 The Journal of the Operational Research Society  
Lin and Makis (2002), adopted a continuous-time hidden Markov chain with a finite state space to describe the state process in a stochastic model with partially observed working states.  ...  state of the system is the root cause of the changes in observed monitoring signals, but not vice versa.  ... 

Page 2050 of Mathematical Reviews Vol. , Issue 87d [page]

1987 Mathematical Reviews  
J. 87d:62157 Optimal online detection of parameter changes in two linear models. Stochastic Process. Appl. 20 (1985), no. 2, 343-351.  ...  Optimal detection rules are derived in the case of detecting a shift in the mean of an autoregressive process and in the case of detecting a change in the regression coefficient with serially correlated  ... 

Continual Learning for Infinite Hierarchical Change-Point Detection [article]

Pablo Moreno-Muñoz, David Ramírez, Antonio Artés-Rodríguez
2019 arXiv   pre-print
Change-point detection (CPD) aims to locate abrupt transitions in the generative model of a sequence of observations.  ...  For this model we derive a continual learning mechanism that is based on the sequential construction of the CRP and the expectation-maximization (EM) algorithm with a stochastic maximization step.  ...  The Bayesian online change-point detection (BOCPD) approach [7] used this idea for recursively performing density estimation, which yields a more robust detection process as the propagation of uncertainty  ... 
arXiv:1910.10087v1 fatcat:6c7htfszajh7vkjwoibme5tj5u

Towards a Fast Detection of Opponents in Repeated Stochastic Games [chapter]

Pablo Hernandez-Leal, Michael Kaisers
2017 Lecture Notes in Computer Science  
Our results show fast detection of the opponent from its behavior, obtaining higher average rewards than the state-of-the-art baseline Pepper in repeated stochastic games.  ...  with changing counter-parties.  ...  The steps of Bayes-Pepper online detection phase are described in Algorithm 3.  ... 
doi:10.1007/978-3-319-71682-4_15 fatcat:ksq7drp2frhblinmbyoyi3kqbm

Pricing average price advertising options when underlying spot market prices are discontinuous

Bowei Chen, Mohan Kankanhalli
2018 IEEE Transactions on Knowledge and Data Engineering  
Advertising options have been recently studied as a special type of guaranteed contracts in online advertising, which are an alternative sales mechanism to real-time auctions.  ...  The former leads to a biased calculation of option payoff and the latter is invalid empirically for many online advertising slots.  ...  To detect volatility clustering, two commonly used methods are: (i) the ACF of absolute log change rates; and (ii) the ACF of squared log change rates.  ... 
doi:10.1109/tkde.2018.2867027 fatcat:jni7fzfigfbb5nt7adfmbaucka
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