The R package spatstat provides a very flexible and useful framework for analysing spatial point patterns. A fundamental feature is a procedure for fitting spatial point process models depending on covariates. However, in practice one often faces incomplete observation of the covariates and this...

We introduce two new variance estimation procedures that use non-overlapping and overlapping blocks, respectively. The non-overlapping blocks estimator can be viewed as the limit of the thinned block bootstrap estimator recently proposed in Guan Loh (2007), by letting the number of thinned...

We introduce a formal testing procedure to assess the fit of an inhomogeneous spatial Poisson process model, based on a discrepancy measure function <inline-formula><inline-graphic xlink:href="asn045ilm1.gif" xmlns:xlink="http://www.w3.org/1999/xlink"/></inline-formula> that is constructed from residuals obtained from the fitted model. We derive the asymptotic distributional properties of <inline-formula><inline-graphic xlink:href="asn045ilm2.gif" xmlns:xlink="http://www.w3.org/1999/xlink"/></inline-formula> and develop a test...

We introduce a new estimation method for parametric intensity function models of inhomogeneous spatial point processes based on weighted estimating equations. The weights can incorporate information on both inhomogeneity and dependence of the process. Simulations show that significant efficiency...