Maximum pseudolikelihood estimator for exponential family models of   marked Gibbs point processes
  This paper is devoted to the estimation of a vector $\bm {\theta}$ parametrizing an energy function of a Gibbs point process, via the maximum pseudolikelihood method. Strong consistency and asymptotic normality results of this estimator depending on a single realization are presented. In the framework of exponential family models, sufficient conditions are expressed in terms of the local energy function and are verified on a wide variety of examples. 
Jean-Michel Billiot, Jean-Fran\c{c}ois Coeurjolly, R\'emy Drouilhet