ABSTRACT
Point processes provide models for point patterns, with complete spatial randomness (CSR) being the simplest theoretical model. CSR assumes that events have an equal likelihood of occurring anywhere within the study area, independent of the locations of other events, which is represented by the homogeneous Poisson process. While most processes deviate from CSR to some degree, CSR remains important in investigations, as it helps differentiate between regular and clustered patterns. In a random pattern, the distribution of each point is independent of the distribution of the others, and points neither inhibit nor promote one another. Regular patterns have more spacing between points that in a random pattern, possibly due to mechanisms such as competition preventing close occurrences. The function quadrat.test() performs a test of CSR for a given point pattern. The first argument can be a point pattern of class ppp or the results of applying quadratcount() to a point pattern.
