ABSTRACT

Acknowledgments ......................................................................................................................335 References.....................................................................................................................................335

This chapter considers inference procedures for parametric spatial point process models. The widespread use of sensible but ad hoc methods based on functional summary statistics has through the past two decades been complemented by likelihood-based methods for parametric spatial point process models. The increasing development of such likelihood-based methods, whether frequentist or Bayesian, has led to more objective and efficient statistical procedures for parametric inference. When checking a fitted parametric point process model, summary statistics and residual analysis play an important role in combination with simulation procedures, as discussed in Chapter 5.