Tabular data from statistical institutes and agencies are mostly 
    confidential and must be protected prior to publications. The cell-key 
    method is a post-tabular Statistical Disclosure Control perturbation 
    technique that adds random noise to tabular data. The statistical 
    properties of the perturbations are defined by some noise probability 
    distributions - also referred to as perturbation tables. 
    This tool can be used to create the perturbation tables based on a maximum 
    entropy approach as described for example in Giessing (2016) 
    <doi:10.1007/978-3-319-45381-1_18>. The perturbation tables created can 
    finally be used to apply a cell-key method to frequency count or magnitude 
    tables.

A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP with these extensions.

We provide inference for personalized medicine models. Namely, we answer the questions: (1) how much better does a purported personalized recommendation engine for treatments do over a business-as-usual approach and (2) is that difference statistically significant?

Evaluates the strength of a surrogate marker by estimating the proportion of treatment effect explained (PTE) and relative power(RP) for the optimally-transformed version of the surrogate.  Details available in Wang et al (2022) <arXiv:2209.08414>.

Function pip3d() tests whether a point in 3D space is
  within, exactly on, or outside an enclosed surface defined by a triangular mesh.
  Function pip2d() tests whether a point in 2D space is within, exactly on, or outside a polygon.
  For a reference, see: Liu et al., A new point containment test algorithm based on preprocessing
  and determining triangles, Computer-Aided Design 42(12):1143-1150.

Permute treatment labels for taxa and environmental gradients to
    generate an empirical distribution of change points.  This is an extension
    for the 'TITAN2' package <https://cran.r-project.org/package=TITAN2>.