Programmatically access the 'Quickbase' JSON API <https://developer.quickbase.com>. 
    You supply parameters for an API call, 'qbr' delivers an http request to the 
    API endpoint and returns its response. Outputs follow 'tidyverse' philosophy.

An extensive set of functions to perform Qualitative Comparative Analysis:
       crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA')
       and fuzzy sets ('fsQCA'), using a GUI - graphical user interface.
       'QCA' is a methodology that bridges the qualitative and quantitative
       divide in social science research. It uses a Boolean minimization
       algorithm, resulting in a minimal causal configuration associated
       with a given phenomenon.

Researchers working with Qualitative Comparative Analysis (QCA)
    can use the package to estimate power of a sufficient term
    using permutation tests. A term can be anything: A condition, conjunction or 
    disjunction of any combination of these. The package further allows users to plot 
    the estimation results and to estimate the number of cases required to achieve a
    certain level of power, given a prespecified null and alternative hypothesis.
    Reference for the article introducing power estimation for QCA is: 
    Rohlfing, Ingo (2018) <doi:10.1017/pan.2017.30> 
    (ungated version: <doi:10.17605/OSF.IO/PC4DF>).

Provides advanced functionality for performing configurational comparative research with Qualitative Comparative Analysis (QCA), including crisp-set, multi-value, and fuzzy-set QCA. It also offers advanced tools for sensitivity diagnostics and methodological evaluations of QCA.

Helper functions for Qualitative Comparative Analysis: evaluate and
    plot Boolean formulae on fuzzy set score data, apply Boolean operations, compute
    consistency and coverage measures.

Quasi-Cauchy quantile regression, proposed by de Oliveira, Ospina, Leiva, Figueroa-Zuniga and Castro (2023) <doi:10.3390/fractalfract7090667>. This regression model is useful for the case where you want to model data of a nature limited to the intervals [0,1], (0,1], [0,1) or (0,1) and you want to use a quantile approach.