#' nos: A package for calculating node overlap and segregation in ecological
#' networks
#'
#' @name nos-package
#' @docType package
#'
#' @description A package to calculate NOS (node overlap and segregation) and
#' the associated metrics described in Strona and Veech (2015) and Strona et
#' al. (2017). The functions provided in the package enable assessment of
#' structural patterns ranging from complete node segregation to perfect
#' nestedness in a variety of network types. In addition, they provide a
#' measure of network modularity.
#'
#' Does not currently work on Macs (OS X El Capitan) as the dependent
#' gmp package is not yet available in binary form for OS X El Capitan.
#'
#' @details There are five main S3 generics that the user can choose depending
#' on whether a directed, bipartite or undirected network is provided as
#' input, and whether a network of potential interactions (pot_net) is
#' available from the user. These five functions are: 1) NOSM_dir - for
#' directed unimode networks (e.g. food webs) when pot_net is not provided, 2)
#' NOSM_undir - for undirected networks (e.g. co-occurrence networks) when
#' pot_net is not provided, 3) NOSM_bip - for bipartite networks (e.g.
#' plant-pollinator networks), 4) NOSM_pot_dir - for directed unimode (e.g.
#' food webs) and bipartite networks when pot_net is provided, and 5)
#' NOSM_pot_undir - for undirected networks (e.g. co-occurrence networks) when
#' pot_net is provided.
#'
#' Each of these five main functions produces an output with class 'NOSM'. An
#' S3 method (summary.NOSM) provides the summary statistics of interest (e.g..
#' NOS, Mod/network modularity, effect size Z, and p-value).
#'
#' If a network of potential interactions is not provided, the computation will
#' be made according to the following criteria: in an undirected network, all
#' nodes will be considered as potential interacting partners; in a directed,
#' unimode network, all nodes having at least an in-coming link will be
#' considered as potential partners for nodes having at least an out-going link
#' and vice-versa; in a bipartite network, where nodes can be formally
#' categorized into two distinct categories (e.g. plant-pollinators) all nodes
#' in one category will be considered as potential partners for the nodes in
#' the other category (and vice-versa).
#'
#' Input data should be in the form of an edge list or frequency interaction
#' matrix (this can be either a bipartite graph type or a squared adjacency
#' matrix type). If the input data are in the format of a frequency interaction
#' matrix, as used in the \link[bipartite]{bipartite} R package, then
#' \code{\link{freqMat_2_edge}} should be used first, to convert the
#' interaction matrix to an edge list prior to running any 'nos' functions.
#'
#' The internal function comb calculates factorials. If the user provided
#' n or k are too large (> roughly 170) factorial(n || k) produces Inf.
#' In these cases gmp::factorialZ is used instead. See the help documentation
#' for the 'gmp' package for further information.
#'
#' It should be noted that due to differences in the way R and Python calculate
#' the standard deviation, the modularity values and z values calculated using
#' this R package differ very slightly (less than 0.2) from the values
#' calculated using the Python scrip from Strona et al. (2017).
#'
#' @author Thomas J. Matthews and Giovanni Strona
#' @references Strona, G., Matthews, T.J., Kortsch, S. and Veech, J.A. (2017)
#' NOS: A software suite to compute node overlap and segregation in
#' ecological networks. Ecography. In review.
NULL
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