OPTIMAL CHANGE-POINT DETECTION IN TREND MODELS WITH INTEGRATED MOVING AVERAGE ERRORS

2002 ◽  
Vol 21 (1-2) ◽  
pp. 99-107
Author(s):  
H. J. Vaman ◽  
K. Suresh Chandra
Keyword(s):  
Change Point ◽  
Moving Average ◽  
Change Point Detection ◽  
Point Detection ◽  
Optimal Change ◽  
Moving Average Errors

Change point detection in social networks using a multivariate exponentially weighted moving average chart

2019 ◽  
Vol 46 (6) ◽  
pp. 790-809
Author(s):  
Ali Salmasnia ◽  
Mohammadreza Mohabbati ◽  
Mohammadreza Namdar
Keyword(s):  
Social Networks ◽  
Control Chart ◽  
Change Point ◽  
Moving Average ◽  
Change Point Detection ◽  
Network Density ◽  
Exponentially Weighted Moving Average ◽  
The Social ◽  
Point Detection ◽  
Weighted Moving Average

Although the significant role of social networks in communications between individuals has attracted researchers’ attention to the social networks, only few authors investigated social network monitoring in their studies. Most of the existing studies in this context suffer from the following three main drawbacks: (1) using the case-based network attributes such as person experiences and departments instead of the main attributes such as network density and centrality attributes, (2) monitoring the social attributes separately with the assumption that they are independent of each other and (3) ignoring detection of real time of change in the network. To overcome the above-mentioned disadvantages, this research develops a statistical method for monitoring the connections among actors in the social networks with the four most important network attributes consisting of (1) network density, (2) degree centrality, (3) betweenness centrality and (4) closeness centrality. To this end, a multivariate exponentially weighted moving average (MEWMA) control chart is used for simultaneous monitoring of these four correlated attributes. Furthermore, since the control chart usually does not alert a signal in the exact time of change due to type II error, this study presents a change point detection method to reduce cost and time required for diagnosing the control chart signal. Eventually, the efficiency of the proposed approach in comparison with the existing methods is evaluated through a simulation procedure. The results indicate that the suggested method has better performance than the univariate approach in detecting change point.

scholarly journals Optimal change point detection in Gaussian processes

2018 ◽  
Vol 193 ◽  
pp. 151-178 ◽  
Author(s):  
Hossein Keshavarz ◽  
Clayton Scott ◽  
XuanLong Nguyen
Keyword(s):  
Gaussian Processes ◽  
Change Point ◽  
Change Point Detection ◽  
Point Detection ◽  
Optimal Change
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