Journal
PHYSICAL REVIEW E
Volume 101, Issue 4, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.101.043305
Keywords
-
Categories
Funding
- Swiss National Science Foundation [105218-179175]
- Swiss National Science Foundation (SNF) [105218_179175] Funding Source: Swiss National Science Foundation (SNF)
Ask authors/readers for more resources
The identification of Hawkes-like processes can pose significant challenges. Despite substantial amounts of data, standard estimation methods show significant bias or fail to converge. To overcome these issues, we propose an alternative approach based on an expectation-maximization algorithm, which instrumentalizes the internal branching structure of the process, thus improving convergence behavior. Furthermore, we show that our method provides a tight lower bound for maximum-likelihood estimates. The approach is discussed in the context of a practical application, namely the collection of outstanding unsecured consumer debt.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available