Implements the Single Transferable Vote (STV) electoral system, with
    clear explanatory graphics. The core function stv() uses Meek's method, the purest
    expression of the simple principles of STV, but which requires electronic
    counting. It can handle votes expressing equal preferences for subsets of
    the candidates. A function stv.wig() implementing the Weighted Inclusive
    Gregory method, as used in Scottish council elections, is also provided,
    and with the same options, as described in the manual. The required vote
    data format is as an R list: a function pref.data() is provided to transform
    some commonly used data formats into this format.
    References for methodology:
    Hill, Wichmann and Woodall (1987) <doi:10.1093/comjnl/30.3.277>,
    Hill, David (2006) <https://www.votingmatters.org.uk/ISSUE22/I22P2.pdf>,
    Mollison, Denis (2023) <arXiv:2303.15310>,
    (see also the package manual pref_pkg_manual.pdf).

Allows users to derive multi-objective weights from pairwise comparisons, which
    research shows is more repeatable, transparent, and intuitive other techniques. These weights
    can be rank existing alternatives or to define a multi-objective utility function for optimization.

Design and analyze two-stage randomized trials with a continuous
    outcome measure. The package contains functions to compute the required 
    sample size needed to detect a given preference, treatment, and selection 
    effect; alternatively, the package contains functions that can report the 
    study power given a fixed sample size. Finally, analysis functions are 
    provided to test each effect using either summary data (i.e. means, 
    variances) or raw study data <doi:10.18637/jss.v094.c02>.

Convenient structures for creating, sourcing, reading, writing
  and manipulating ordinal preference data. Methods for writing to/from PrefLib
  formats. See Nicholas Mattei and Toby Walsh "PrefLib: A Library of Preference
  Data" (2013) <doi:10.1007/978-3-642-41575-3_20>.