Wrangle and annotate different types of political texts.
    It also introduces Urgency Analysis,
    a new method for the analysis of urgency in political texts.

Tools for simplifying the creation and management of data structures
    suitable for dealing with policy portfolios, that is, two-dimensional spaces 
    of policy instruments and policy targets. The package also allows to generate measures of
    portfolio characteristics and facilitates their visualization.

Learn optimal policies via doubly robust empirical
 welfare maximization over trees. Given doubly robust reward estimates, this package
 finds a rule-based treatment prescription policy, where the policy takes the form of
 a shallow decision tree that is globally (or close to) optimal.

This is a collection of data and functions for common metrics in political science research. Data measuring ideology, and functions calculating geographical diffusion and ideological diffusion - geog.diffuse() and ideo.dist(), respectively. Functions derived from methods developed in: Soule and King (2006) <doi:10.1086/499908>, Berry et al. (1998) <doi:10.2307/2991759>, Cruz-Aceves and Mallinson (2019) <doi:10.1177/0160323X20902818>, and Grossback et al. (2004) <doi:10.1177/1532673X04263801>.

Bundles the datasets and functions used in the textbook by Philip
    Pollock and Barry Edwards, an R Companion to Essentials of Political Analysis,
    Second Edition.

Set of functions to polish content for Microsoft 'Word' and 'PowerPoint' 
    into 'OOXML'. Polishing is the conversion of the R object into an 'OOXML'
    representation of the object that can then be added to 'Word' or 'PowerPoint' 
    files.

Authentication, user administration, hosting, and additional infrastructure for 'shiny' apps. See
  <https://polished.tech> for additional documentation and examples.

A very small package for more convenient use of 'NaileR'. You provide a data set containing a latent variable you want to understand. It generates a description and an interpretation of this latent variable using a Large Language Model. For perceptual data, it describes the stimuli used in the experiment.