A collection of functions for the manipulation and
 analysis of arbitrarily dimensioned arrays.  The original motivation
 for the package was the development of efficient, vectorized
 algorithms for the creation and investigation of magic squares and
 high-dimensional magic hypercubes.

Functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots.

Magic functions to obtain results from for loops.

Bindings to 'ImageMagick': the most comprehensive open-source image
    processing library available. Supports many common formats (png, jpeg, tiff,
    pdf, etc) and manipulations (rotate, scale, crop, trim, flip, blur, etc).
    All operations are vectorized via the Magick++ STL meaning they operate either
    on a single frame or a series of frames for working with layers, collages,
    or animation. In RStudio images are automatically previewed when printed to
    the console, resulting in an interactive editing environment. The latest 
    version of the package includes a native graphics device for creating 
    in-memory graphics or drawing onto images using pixel coordinates.

Enables us to use the functions of the package 'magick' interactively.

Set of utility functions to interact with 'WeMo Switch', a smart 
    plug that can be remotely controlled via wifi. The provided functions make 
    it possible to turn one or more 'WeMo Switch' plugs on and off in a 
    scriptable fashion. More information about 'WeMo Switch' can be found at 
    <http://www.belkin.com/us/p/P-F7C027/>.

Balancing quasi-experimental field research for effects of covariates is fundamental for drawing causal inference. Propensity Score Matching deals with this issue but current
    techniques are restricted to binary treatment variables. Moreover, they provide several solutions without providing a comprehensive framework on choosing the best model. The
    'MAGMA.R' -package addresses these restrictions by offering nearest neighbor matching for two to four groups. It also includes the option to match data of a 2x2 design. In addition, 
    'MAGMA.R' includes a framework for evaluating the post-matching balance. The package includes functions for the matching process and matching reporting. We provide a tutorial on 
    'MAGMA.R' as vignette. More information on 'MAGMA.R' can be found in Feuchter, M. D., Urban, J., Scherrer V., Breit, M. L., and Preckel F. (2022) <https://osf.io/p47nc/>.