Description: Provides methods for organizing data in a hypercube
(i.e. a multi-dimensional cube). Cubes are generated from molten data frames.
Each cube can be manipulated with five operations: rotation (changeDimensionOrder()),
dicing and slicing (add.selection(), remove.selection()), drilling down (add.aggregation()),

(i.e., a multi-dimensional cube). Cubes are generated from molten data frames.
Each cube can be manipulated with five operations: rotation (change.dimensionOrder()),

Description: Provides functions and methods for organizing data in hypercubes

Title: A generalization of the Dirichlet distribution
Depends: R (>= 2.7.0), adapt, methods, aylmer, abind, mvtnorm
Description: A suite of routines for the hyperdirichlet distribution
Packaged: Sun Nov 23 22:55:16 2008; rksh

Packaged: Sat Jan 17 22:14:13 2009; rksh

Packaged: Sat Apr 11 21:33:34 2009; rksh

Depends: R (>= 2.7.0), methods, aylmer, abind, mvtnorm

Depends: R (>= 2.7.0), methods, aylmer, abind, mvtnorm, cubature

Title: A Generalization of the Dirichlet Distribution
Description: A suite of routines for the hyperdirichlet distribution.

Title: Machine Learning of Hyperrectangular Gating Strategies for
Description: Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs. For more details see Etienne Becht, Yannick Simoni, Elaine Coustan-Smith, Maximilien Evrard, Yang Cheng, Lai Guan Ng, Dario Campana and Evan Newell (2018) <doi:10.1101/278796>.
Imports: stats, grDevices, utils, graphics, lattice
Suggests: knitr, rmarkdown, flowCore, sp, rgeos

Description: Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs.
Imports: stats, grDevices, utils, graphics