Distribution of Largest Root for Single and Double Wishart Settings

Functions for hypothesis testing in single and double Wishart settings, based on Roy's largest root. This test statistic is especially useful in multivariate analysis. The computations are based on results by Chiani (2014) and Chiani (2016) . They use the fact that the CDF is related to the Pfaffian of a matrix that can be computed in a finite number of iterations. This package takes advantage of the Boost and Eigen C++ libraries to perform multi-precision linear algebra.

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R package that implements Chiani's iterative algorithms for computing the distribution of the largest root in single and double Wishart settings.


This package is now available on CRAN. Alternatively, you can install from GitHub using the devtools package:



rootWishart 0.4.1

  • Fix NOTE from R-devel
  • Add testing suite

rootWishart 0.4.0

  • Register native routines
  • Parameter mprec has been removed. The type of precision is now controlled by the parameter type.
    • type = 'double' gives double precision
    • type = 'multi' gives multiprecision
  • The default behaviour when type is unspecified is to decide adaptively based on the input parameters which type of precision to choose.

rootWishart 0.3.0

  • First release

Reference manual

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0.4.1 by Maxime Turgeon, 3 years ago


Report a bug at http://github.com/turgeonmaxime/rootWishart/issues

Browse source code at https://github.com/cran/rootWishart

Authors: Maxime Turgeon [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp

Suggests testthat

Linking to Rcpp, RcppEigen, BH

See at CRAN