Generates interactive bipartite graphs using the D3 library.
    Designed for use with the 'bipartite' analysis package.
    Includes open source 'viz-js' library 
    Adapted from examples at <https://bl.ocks.org/NPashaP> (released under GPL-3).

Function bipmod() that partitions a bipartite network into non-overlapping biclusters by maximizing bipartite modularity defined in Barber (2007) <doi:10.1103/PhysRevE.76.066102> using the bipartite version of the algorithm described in Treviño (2015) <doi:10.1088/1742-5468/2015/02/P02003>.

We use a Bayesian approach to run individual patient data meta-analysis and network meta-analysis using 'JAGS'. The methods incorporate shrinkage methods and calculate patient-specific treatment effects as described in Seo et al. (2021) <DOI:10.1002/sim.8859>. This package also includes user-friendly functions that impute missing data in an individual patient data using mice-related packages.

A modern view on the principal component analysis biplot with 
    calibrated axes. Create principal component analysis biplots rendered in 
    HTML with significant reactivity embedded within the plot. Furthermore, 
    the traditional biplot view is enhanced by translated axes with inter-class
    kernel densities superimposed. For more information on biplots, see 
    Gower, J.C., Lubbe, S. and le Roux, N.J. (2011, ISBN: 978-0-470-01255-0).

A GUI with which the user can construct and interact with Bootstrap methods on Classical Biplots and with Clustering and/or Disjoint Biplot. This GUI is also aimed for estimate any numerical data matrix using the Clustering and Disjoint Principal component (CDPCA) methodology.

Provides users with an EZ-to-use platform for representing data
             with biplots. Currently principal component analysis (PCA), canonical variate
             analysis (CVA) and simple correspondence analysis (CA) biplots are included. 
             This is accompanied by various formatting
             options for the samples and axes. Alpha-bags and concentration ellipses
             are included for visual enhancements and interpretation. For an extensive
             discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J.
             (2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester.