Results 221 to 230 of about 920,349 (257)

Change Point Detection

2021
In situ TEM and other dynamic imaging instruments alter the landscape of materials science and engineering. The unique and unprecedented ability to observe the transformation of nanoscale objects as it occurs is unparalleled in comparison to other material characterization methods, and is of tremendous value to material scientists and engineers who ...
Chiwoo Park, Yu Ding
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Multiscale Change Point Detection

Theory of Probability & Its Applications, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Suvorikova, A., Spokoiny, V.
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Self-Normalized Sequential Change-point Detection

Statistica Sinica, 2021
This article introduces a new sequential monitoring scheme for detecting change-points in general time series models which achieves an asymptotically exact Type-I error while at the same time it avoids estimation of the long-run variance. The key concept is the introduction of a self-normalizer (SN) to replace the long-run variance estimator when ...
Chan, Ngai Hang, Ng, Wai Leong, Yau, Chun Yip   +2 more
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Parallelization of Change Point Detection

The Journal of Physical Chemistry A, 2017
The change point detection method ( Watkins , L. P. ; Yang , H. J. Phys. Chem. B 2005 , 109 , 617 ) allows the objective identification and isolation of abrupt changes along a data series. Because this method is grounded in statistical tests, it is particularly powerful for probing complex and noisy signals without artificially imposing a kinetics ...
Nancy Song, Haw Yang
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Change‐point detection in panel data

Journal of Time Series Analysis, 2012
We consider N panels and each panel is based on T observations. We are interested to test if the means of the panels remain the same during the observation period against the alternative that the means change at an unknown time. We provide tests which are derived from a likelihood argument and they are based on the adaptation of the CUSUM method to ...
Horváth, Lajos, Hušková, Marie
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Change Point Detection Techniques

2004
In this chapter we will discuss change point detection techniques for analyzing population change over time. The linkage between information theory and statistics has been discussed in Chapter 5. In statistics, the problem of change point analysis can be formulated as that of model selection.
Bon K. Sy, Arjun K. Gupta
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Change-Point Detection in Angular Data

Annals of the Institute of Statistical Mathematics, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Grabovsky, Irina, Horváth, Lajos
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NONPARAMETRIC TRUNCATED SEQUENTIAL CHANGE-POINT DETECTION

Statistics & Risk Modeling, 1995
Summary: New nonparametric truncated sequential changepoint detection processes are considered via a theorem of \textit{D. A. Darling} and \textit{P. Erdős} [Duke Math. J. 23, 143-155 (1956; Zbl 0070.138)]. Their asymptotic and finite sample properties are examined and compared to existing procedures.
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Hubness Change Point Detection

Proceedings of the AAAI Conference on Artificial Intelligence
This study proposes a new change detection method that leverages hubness. Hubness is a phenomenon that occurs in high-dimensional spaces, where certain special data points, known as hub data, tend to be closer to other data points. Hubness is known to degrade the accuracy of methods based on nearest neighbor search.
Ikumi Suzuki, Kazuo Hara, Eiji Murakami
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