Towards optimal Takacs--Fiksel estimation
Statistics Theory
2016-07-14 v3 Statistics Theory
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.
Cite
@article{arxiv.1512.06693,
title = {Towards optimal Takacs--Fiksel estimation},
author = {Jean-François Coeurjolly and Yongtao Guan and Mahdieh Khanmohammadi and Rasmus Waagepetersen},
journal= {arXiv preprint arXiv:1512.06693},
year = {2016}
}