Provides statistical methods for auditing as implemented in JASP
    for Audit (Derks et al., 2021 <doi:10.21105/joss.02733>). First, the package
    makes it easy for an auditor to plan a statistical sample, select the sample
    from the population, and evaluate the misstatement in the sample compliant
    with international auditing standards. Second, the package provides
    statistical methods for auditing data, including tests of digit
    distributions and repeated values. Finally, the package includes methods for
    auditing algorithms on the aspect of fairness and bias. Next to classical
    statistical methodology, the package implements Bayesian equivalents of
    these methods whose statistical underpinnings are described in Derks et al.
    (2021) <doi:10.1111/ijau.12240>, Derks et al. (2024)
    <doi:10.2308/AJPT-2021-086>, Derks et al. (2022) <doi:10.31234/osf.io/8nf3e>
    Derks et al. (2024) <doi:10.31234/osf.io/tgq5z>, and Derks et al. (2025)
    <doi:10.31234/osf.io/b8tu2>.

Offer procedures to download financial-economic time series data and enhanced procedures for computing the investment performance indices of Bacon (2004) <DOI:10.1002/9781119206309>.

Provides functions to extract joint planes from 3D triangular mesh derived
             from point cloud and makes data available for structural analysis.

Java GUI for R - cross-platform, universal and unified Graphical User Interface for R. For full functionality on Windows and Mac OS X JGR requires a start application which depends on your OS.

All datasets and functions used in the german book "Statistik mit R und RStudio" by grosse Schlarmann (2010-2024) <https://www.produnis.de/R/>.

An R package that implements the JICO algorithm [Wang, P., Wang, H., Li, Q., Shen, D., & Liu, Y. (2024). <Journal of Computational and Graphical Statistics, 33(3), 763-773>]. 
        It aims at solving the multi-group regression problem. The algorithm decomposes the responses from multiple groups into shared and group-specific
        components, which are driven by low-rank approximations of joint and individual structures from the covariates respectively.