Parameter estimation for growth interaction processes using spatio-temporal information
Artikel i vetenskaplig tidskrift, 2013

Methods for the parameter estimation for a spatio-temporal marked point process model, the so-called growth-interaction model, are investigated. Least squares estimation methods for this model found in the literature are only concerned with fitting the mark distribution observed in the data. These methods are unable to distinguish between models which have the same birth, death, interaction and growth functions and parameters but different arrival strategies for the points. Hence, they are extended such that the spatial structure of a point pattern is also taken into account. The suggested methods are evaluated in a simulation study and applied to a small data set from forestry.

Least squares estimation

Logistic power-law function


Parameter estimation



Scots pines


Claudia Redenbach

Technische Universitat Kaiserslautern

Aila Särkkä

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Computational Statistics and Data Analysis

0167-9473 (ISSN)

Vol. 57 672-683