Spatial sampling and censoring

Abstract

When a spatial pattern is observed through a bounded window, inference about the pattern is hampered by sampling eeects known as \edge eeects". This chapter identiies two main types of edge eeects: size-dependent sampling bias and censoring eeects. Sampling bias can be eliminated by changing the sampling technique, or`corrected' by weighting the observations. Censoring eeects can be tackled using the methods of survival analysis.