Sequential Changepoint Approach for Online Community Detection
نویسندگان
چکیده
منابع مشابه
Bayesian Online Changepoint Detection
Changepoints are abrupt variations in the generative parameters of a data sequence. Online detection of changepoints is useful in modelling and prediction of time series in application areas such as finance, biometrics, and robotics. While frequentist methods have yielded online filtering and prediction techniques, most Bayesian papers have focused on the retrospective segmentation problem. Her...
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Changepoints have been extensively analysed in order to identify structural changes in time series data, typically when the data are of known parametric form. This report presents an exploration of methods to detect changepoints in a nonparametric setting, where no assumptions are made with regard to the distributional structure of the data, yet must still maintain a specified level of performa...
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Suppose a process yields independent observations whose distributions belong to a family parameterized by θ ∈Θ. When the process is in control, the observations are i.i.d. with a known parameter value θ0. When the process is out of control, the parameter changes. We apply an idea of Robbins and Siegmund [Proc. Sixth Berkeley Symp. Math. Statist. Probab. 4 (1972) 37–41] to construct a class of s...
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ژورنال
عنوان ژورنال: IEEE Signal Processing Letters
سال: 2015
ISSN: 1070-9908,1558-2361
DOI: 10.1109/lsp.2014.2381553