The EXPOS model uses a digital elevation model (DEM) to estimate
    exposed and protected areas for a given hurricane wind direction and
    inflection angle. The resulting topographic exposure maps can be combined
    with output from the HURRECON model to estimate hurricane wind damage
    across a region. For details on the original version of the EXPOS model
    written in 'Borland Pascal', see: Boose, Foster, and Fluet (1994)
    <doi:10.2307/2937142>, Boose, Chamberlin, and Foster (2001)
    <doi:10.1890/0012-9615(2001)071[0027:LARIOH]2.0.CO;2>, and Boose,
    Serrano, and Foster (2004) <doi:10.1890/02-4057>.

Produces diversity estimates and species lists with associated global distribution for any vascular plant family and genus from 'Plants of the World Online' database <https://powo.science.kew.org/>, by interacting with the source code of each plant taxon page. It also creates global maps of species richness, graphics of species discoveries and nomenclatural changes over time.

A set of functions for computing expected permutation matrices given a matrix of likelihoods for each individual assignment. It has been written to accompany the forthcoming paper 'Computing expectations and marginal likelihoods for permutations'. Publication details will be updated as soon as they are finalized.

Allows to calculate the probabilities  of occurrences of an event in a 
 great number of repetitions of Bernoulli experiment, through the application of  
 the local and the integral theorem of De Moivre Laplace, and the theorem of Poisson. 
 Gives the possibility to show the results graphically and analytically, and to compare
 the results obtained by the application of the above  theorems with those calculated by
 the direct application of the Binomial formula. Is basically useful for educational
 purposes.

Given a continuous-time dynamic network, this package allows one to fit a stochastic blockmodel where nodes belonging to the same group create interactions and non-interactions of similar lengths. This package implements the methodology described by R. Rastelli and M. Fop (2019) <arXiv:1901.09828>.