A functional central limit theorem for the K-function with an estimated intensity function

The K-function is arguably the most important functional summary statistic for spatial point processes. It is used extensively for goodness-of-fit testing and in connection with minimum contrast estimation for parametric spatial point process models. It is thus pertinent to understand the asymptotic properties of estimates of the K-function. In this paper we derive the functional asymptotic distribution for the K-function estimator. Contrary to previous papers on functional convergence we consider the case of an inhomogeneous intensity function. We moreover handle the fact that practical K-function estimators rely on plugging in an estimate of the intensity function. This removes two serious limitations of the existing literature.