Infill asymptotics for logistic regression estimators for spatio-temporal point processes

Marie-Colette van Lieshout, Changqing Lu*

*Corresponding author for this work

Research output: Working paperPreprintAcademic

30 Downloads (Pure)

Abstract

This paper discusses infill asymptotics for logistic regression estimators for spatio-temporal point processes whose intensity functions are of log-linear form. We establish strong consistency and asymptotic normality for the parameters of a Poisson point process model and demonstrate how these results can be extended to general point process models. Additionally, under proper conditions, we also extend our central limit theorem to other unbiased estimating equations that are based on the Campbell--Mecke theorem.
Original languageEnglish
PublisherArXiv.org
Number of pages22
DOIs
Publication statusPublished - 25 Aug 2022

Keywords

  • Campbell--Mecke theorem
  • infill asymptotics
  • logistic regression estimator
  • spatio-temporal point process
  • unbiased estimating equation

Fingerprint

Dive into the research topics of 'Infill asymptotics for logistic regression estimators for spatio-temporal point processes'. Together they form a unique fingerprint.

Cite this