TY - GEN
T1 - Adaptive Online Monitoring of the Ising model
AU - Suh, Namjoon
AU - Zhang, Ruizhi
AU - Mei, Yajun
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Ising model is a general framework for capturing the dependency structure among random variables. It has many interesting real-world applications in the fields of medical imaging, genetics, disease surveillance, etc. Nonetheless, literature on the online change-point detection of the interaction parameter in the model is rather limited. This might be attributed to following two challenges: 1) the exact evaluation of the likelihood function with the given data is computationally infeasible due to the presence of partition function and 2) the post-change parameter usually is unknown. In this paper, we overcome these two challenges via our proposed adaptive pseudo-CUSUM procedure, which incorporates the notion of pseudo-likelihood function under the CUSUM framework. Asymptotic analysis, numerical simulation, and case study corroborate the statistical efficiency and the practicality of our proposed scheme.
AB - Ising model is a general framework for capturing the dependency structure among random variables. It has many interesting real-world applications in the fields of medical imaging, genetics, disease surveillance, etc. Nonetheless, literature on the online change-point detection of the interaction parameter in the model is rather limited. This might be attributed to following two challenges: 1) the exact evaluation of the likelihood function with the given data is computationally infeasible due to the presence of partition function and 2) the post-change parameter usually is unknown. In this paper, we overcome these two challenges via our proposed adaptive pseudo-CUSUM procedure, which incorporates the notion of pseudo-likelihood function under the CUSUM framework. Asymptotic analysis, numerical simulation, and case study corroborate the statistical efficiency and the practicality of our proposed scheme.
UR - http://www.scopus.com/inward/record.url?scp=85077797860&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077797860&partnerID=8YFLogxK
U2 - 10.1109/ALLERTON.2019.8919824
DO - 10.1109/ALLERTON.2019.8919824
M3 - Conference contribution
AN - SCOPUS:85077797860
T3 - 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
SP - 426
EP - 431
BT - 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
Y2 - 24 September 2019 through 27 September 2019
ER -