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R package for hierarchical species distribution models
...Such models allows interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.
...Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”
The R package to be built aims at implementing what I did in a few scripts for the preparation of the papers I published in CaGEO and TGIS (see below). Basically this is related to the computation of the distribution of k co-occurrences of spatial events (generalising the contiguity distributions - 2 co-occurrences at distance 0) to derive spatial clustering statistics (mainly using the Shannon entropy, then called the k-spatial entropy) and methods linked to this: SOOk, SelSOOk (see caGEO paper) and scankOO (see TGIS). Another method (CAkOO) performing a k-Correspondence Analysis (i.e. on a multiway table with k entries) on the contingencies of co-occurrenceshas been already "published in my JSS paper about another R package: PTAk.
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