Implementation of Gibbs sampling algorithm for Bayesian Estimation
    of the Reduced Reparameterized Unified Model ('rrum'), described by 
    Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.

Advanced response surface analysis. The main function RSA computes
    and compares several nested polynomial regression models (full second- or 
    third-order polynomial, shifted and rotated squared difference model, 
    rising ridge surfaces, basic squared difference model, asymmetric or 
    level-dependent congruence effect models). The package provides plotting 
    functions for 3d wireframe surfaces, interactive 3d plots, and contour plots. 
    Calculates many surface parameters (a1 to a5, principal axes, stationary point,
    eigenvalues) and provides standard, robust, or bootstrapped standard errors
    and confidence intervals for them.

The package contains all the data sets related to the book
        written by the maintainer of the package.

Empirical best linear unbiased prediction (EBLUP) and
    robust prediction of the area-level means under the basic unit-level
    model. The model can be fitted by maximum likelihood or a (robust)
    M-estimator. Mean square prediction error is computed by a parametric
    bootstrap.

Provides a model agnostic tool for white-box model trained on features extracted from a black-box model. For more information see: Gosiewska et al. (2020) <doi:10.1016/j.dss.2021.113556>.

Provides access to geocomputing and terrain analysis
    functions of the geographical information system (GIS) 'SAGA' (System
    for Automated Geoscientific Analyses) from within R by running the
    command line version of SAGA. This package furthermore provides
    several R functions for handling ASCII grids, including a flexible
    framework for applying local functions (including predict methods of
    fitted models) and focal functions to multiple grids. SAGA GIS is
    available under GPL-2 / LGPL-2 licences from
    <https://sourceforge.net/projects/saga-gis/>.