'Olm' and 'Megolm' encryption ratchet primitives for the
    'Matrix' messaging protocol <https://matrix.org/>, wrapping the
    'vodozemac' Rust crate. Provides device-key generation, one-time-key
    management, 1:1 'Olm' sessions, and 'Megolm' group sessions. Pairs
    with the 'mx.api' package, which handles 'Matrix' HTTP transport.

Computes Control limits, coefficients of control limits, various performance metrics  and depicts control charts for monitoring Maxwell-distributed quality characteristics.

Methods and tools for deriving spatial summary functions from single-cell imaging
  data and performing functional data analyses. Functions can be applied to other single-cell
  technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods
  are in the 'refund' package <https://cran.r-project.org/package=refund> while calculation of the
  spatial summary functions are from the 'spatstat' package <https://spatstat.org/>.

Generates efficient balanced mixed-level k-circulant supersaturated designs by interchanging the elements of the generator vector. Attempts to generate a supersaturated design that has EfNOD efficiency more than user specified efficiency level (mef). Displays the progress of generation of an efficient mixed-level k-circulant design through a progress bar. The progress of 100 per cent means that one full round of interchange is completed. More than one full round (typically 4-5 rounds) of interchange may be required for larger designs. For more details, please see Mandal, B.N., Gupta V. K. and Parsad, R. (2011). Construction of Efficient Mixed-Level k-Circulant Supersaturated Designs, Journal of Statistical Theory and Practice, 5:4, 627-648, <doi:10.1080/15598608.2011.10483735>.

Provides a convenient interface in 'OpenMx' for building
    Estabrook's (2015) <doi:10.1037/a0034523> Measurement Model of
    Derivatives (MMOD).

Implements methods to normalize multiplexed imaging data, including
    statistical metrics and visualizations to quantify technical variation in 
    this data type. Reference for methods listed here: Harris, C., Wrobel, J., 
    & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging 
    Data. Journal of Open Source Software, 7(71), 4180, 
    <doi:10.21105/joss.04180>.