We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. This package implements a Bayesian derivation of the posterior probability distribution of the population size using a binomial likelihood and non-conjugate, discrete uniform priors under sampling with or without replacement. This can be used for a variety of statistical problems involving absolute quantification under uncertainty. See Comoglio et al. (2013) <doi:10.1371/journal.pone.0074388>.

Computes a new measure, DNSL betweenness, via the creation
    of a new graph from an existing one, duplicating nodes
    with self-loops. This betweenness centrality does not drop this
    essential information. Implements
    Merelo & Molinari (2024) <doi:10.1007/s42001-023-00245-4>.

Identifies code blocks that have a high level of similarity
  within a set of R files.

An easy-to-use yet powerful system for plotting grouped data effect sizes.
    Various types of effect size can be estimated, then plotted together with a
    representation of the original data. Select from many possible data representations
    (box plots, violin plots, raw data points etc.), and combine as desired.
    'Durga' plots are implemented in base R, so are compatible with base R methods
    for combining plots, such as 'layout()'. See Khan & McLean (2023) 
    <doi:10.1101/2023.02.06.526960>.

A suite of tools to help modelers and decision-makers effectively
 interpret and communicate decision risk when evaluating multiple policy options.
 It uses model outputs from uncertainty analysis for baseline scenarios and policy
 alternatives to generate visual representations of uncertainty and quantitative
 measures for assessing associated risks. For more details see 
 Wiggins and colleagues (2025) <doi:10.1371/journal.pone.0332522> and <https://dut.ihe.ca/>.

Creates a data frame containing the metadata associated with
    the documentation of a collection of R packages. It allows for linking
    topic names to their corresponding documentation online. If you
    maintain a universe meta-package, it helps create a comprehensive
    reference for its website.