Source estimation in continuous-time diffusion networks via incomplete observation

Chaoyi Shi, Qi Zhang and Tianguang Chu

Physica A: Statistical Mechanics and its Applications, 2022, vol. 592, issue C

Abstract: This paper considers the problem of estimating the source of diffusion in a network under incomplete observation condition. The diffusion process is described by a continuous-time information diffusion model and the source estimation is formulated as a maximum likelihood (ML) estimator in terms of a Gaussian weighted averaging of the correlation coefficients between the observed activation times and the sampled transmission delays obtained by Monte Carlo simulations. Experiments are worked out with both synthetic and real-world networks to show the effectiveness of our method in comparison with previous results.

Keywords: Diffusive network; Source estimation; Transmission delay distribution; Gaussian weighted averaging correlation coefficient; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:592:y:2022:i:c:s0378437121009985

DOI: 10.1016/j.physa.2021.126843

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