Row-clustering of a Point Process-valued Matrix

• URL: http://arxiv.org/abs/2110.01207v1
• Date: Mon, 4 Oct 2021 06:27:26 GMT
• Title: Row-clustering of a Point Process-valued Matrix
• Authors: Lihao Yin and Ganggang Xu and Huiyan Sang and Yongtao Guan
• Abstract summary: We study a matrix whose entries are marked log-Gaussian Cox processes and cluster rows of such a matrix. An efficient semi-parametric Expectation-Solution (ES) algorithm combined with functional principal component analysis (FPCA) of point processes is proposed for model estimation. The effectiveness of the proposed framework is demonstrated through simulation studies and a real data analysis.
• Score: 2.0391237204597363
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Structured point process data harvested from various platforms poses new challenges to the machine learning community. By imposing a matrix structure to repeatedly observed marked point processes, we propose a novel mixture model of multi-level marked point processes for identifying potential heterogeneity in the observed data. Specifically, we study a matrix whose entries are marked log-Gaussian Cox processes and cluster rows of such a matrix. An efficient semi-parametric Expectation-Solution (ES) algorithm combined with functional principal component analysis (FPCA) of point processes is proposed for model estimation. The effectiveness of the proposed framework is demonstrated through simulation studies and a real data analysis.

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