Presence‐only data are widely used for species distribution modelling, and point process
regression models are a flexible tool that has considerable potential for this problem, when …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

Modeling the spatial distribution of a species is a fundamental problem in ecology. A number
of modeling methods have been developed, an extremely popular one being MAXENT, a …

Spatial point processes are mathematical models used to describe and analyse the
geometrical structure of patterns formed by objects that are irregularly or randomly …

spatstat is a package for analyzing spatial point pattern data. Its functionality includes
exploratory data analysis, model-fitting, and simulation. It is designed to handle realistic …

While mapped data provide a common ground for discussions between the public, the
media, regulatory agencies, and public health researchers, the analysis of spatially …

Spatial point processes play a fundamental role in spatial statistics and today they are an
active area of research with many new applications. Although other published works …

entropart: An R Package to Measure and Partition Diversity Page 1 JSS Journal of Statistical
Software October 2015, Volume 67, Issue 8. doi:10.18637/jss.v067.i08 entropart: An R Package …

In this paper we first describe the class of log-Gaussian Cox processes (LGCPs) as models
for spatial and spatio-temporal point process data. We discuss inference, with a particular …

Summary 1 This article reviews the application of some summary statistics from current
theory of spatial point processes for extracting information from spatial patterns of plants …