Towards optimal Takacs–Fiksel estimation

TY - JOUR

T1 - Towards optimal Takacs–Fiksel estimation

AU - Coeurjolly, Jean François

AU - Guan, Yongtao

AU - Khanmohammadi, Mahdieh

AU - Waagepetersen, Rasmus

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Gibbs point processes

KW - Godambe information

KW - Optimal estimation

KW - Pseudolikelihood

KW - Spatial point processes

U2 - 10.1016/j.spasta.2016.08.002

DO - 10.1016/j.spasta.2016.08.002

M3 - Journal article

AN - SCOPUS:84995743991

SN - 2211-6753

VL - 18

SP - 396

EP - 411

JO - Spatial Statistics

JF - Spatial Statistics

IS - Part B

ER -