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arXiv · 1512.06693

Towards optimal Takacs--Fiksel estimation

Jean-François Coeurjolly·Yongtao Guan·Mahdieh Khanmohammadi·Rasmus Waagepetersen
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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.

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Jean-François Coeurjolly, Yongtao Guan, Mahdieh Khanmohammadi, Rasmus Waagepetersen. 2016-07-13. Towards optimal Takacs--Fiksel estimation. https://arxiv.org/abs/1512.06693

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