State estimation for temporal point processes
Methodology
2015-06-04 v1
Abstract
This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point processes. For a range of models, the marginal and conditional distributions are derived. We discuss likelihood based inference as well as parameter estimation using the method of moments, conduct a simulation study for the important special case of renewal processes and analyse a data set collected by Diggle and Hawtin.
Cite
@article{arxiv.1506.01194,
title = {State estimation for temporal point processes},
author = {M. N. M. van Lieshout},
journal= {arXiv preprint arXiv:1506.01194},
year = {2015}
}