Creates an object that stores a matrix ensemble, matrices
  that share the same common properties, where rows and columns can be
  annotated. Matrices must have the same dimension and dimnames. Operators to
  manipulate these objects are provided as well as mechanisms to apply
  functions to these objects.

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds().  Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.  There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

Functions to perform fast statistical hypothesis tests on rows/columns of matrices.
  The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use,
  3) compatibility with tests implemented in R (like those available in the 'stats' package).

An easy-to-use workflow that provides tools to create, update and fill literature matrices commonly used in research, specifically epidemiology and health sciences research. The project is born out of need as an easy–to–use tool for my research methods classes.

An implementation of matrix mathematics wherein operations are performed "by name."

Provides functions to collapse a tidy data frame into matrices in a data frame
    and expand a data frame of matrices into a tidy data frame.

Identifying maturation stages across young athletes is paramount for talent identification. Furthermore, the concept of biobanding, or grouping of athletes based on their biological development, instead of their chronological age, has been widely researched. The goal of this package is to help professionals working in the field of strength & conditioning and talent ID obtain common maturation metrics and as well as to quickly visualize this information via several plotting options. For the methods behind the computed maturation metrics implemented in this package refer to Khamis, H. J., & Roche, A. F. (1994) <https://pubmed.ncbi.nlm.nih.gov/7936860/>, Mirwald, R.L et al., (2002) <https://pubmed.ncbi.nlm.nih.gov/11932580/> and Cumming, Sean P. et al., (2017) <doi:10.1519/SSC.0000000000000281>.