Towards optimal Takacs–Fiksel estimation

Jean François Coeurjolly, Yongtao Guan, Mahdieh Khanmohammadi, Rasmus Waagepetersen

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The Takacs–Fiksel method is a general approach to estimate the parameters of a spatial Gibbs point process. This method embraces standard procedures such as the pseudolikelihood and is defined via weight functions. In this paper we propose a general procedure to find weight functions which reduce the Godambe information and thus outperform pseudolikelihood in certain situations. The new procedure is applied to a standard dataset and to a recent neuroscience replicated point pattern dataset. Finally, the performance of the new procedure is investigated in a simulation study.

Original languageEnglish (US)
Pages (from-to)396-411
Number of pages16
JournalSpatial Statistics
Volume18
DOIs
StatePublished - Nov 1 2016

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Keywords

  • Gibbs point processes
  • Godambe information
  • Optimal estimation
  • Pseudolikelihood
  • Spatial point processes

ASJC Scopus subject areas

  • Statistics and Probability
  • Computers in Earth Sciences
  • Management, Monitoring, Policy and Law

Cite this

Coeurjolly, J. F., Guan, Y., Khanmohammadi, M., & Waagepetersen, R. (2016). Towards optimal Takacs–Fiksel estimation. Spatial Statistics, 18, 396-411. https://doi.org/10.1016/j.spasta.2016.08.002