No. 1110

Title:

Intensity inferences for a partially observed self-similar point process

Author(s):

Zhuang, Jiancang (Institute of Statistical Mathematics)

Key words:

Self-similar point process, partially observed process, filtering, ETAS model

Abstract:

    The likelihood of a point process is determined by its conditional intensity (stochastic intensity conditional on its internal history). The paper concerns with the maximum likelihood estimation problem associated with the self-similar model while the whole process is partially observed.