all C code by F. Panneton, P. L'Ecuyer and M. Matsumoto and R port by Christophe Dutang and Petr Savicky <savicky@cs.cas.cz>.
It is a dedicated package to WELL pseudo random generators, which were introduced in Panneton et al. (2006), ``Improved Long-Period Generators Based on Linear Recurrences Modulo 2'', ACM Transactions on Mathematical Software. But this package is not intended to be used directly, you are strongly __encouraged__ to use the 'randtoolbox' package, which depends on this package.

Toolbox for WELL Random Number Generators
C code by F. Panneton, P. L'Ecuyer and M. Matsumoto and R port by Christophe Dutang and Petr Savicky <savicky@cs.cas.cz>.

C code by F. Panneton [aut], P. L'Ecuyer [aut], M. Matsumoto [aut]
and R port by Christophe Dutang [cre, aut], Petr Savicky [aut] <savicky@cs.cas.cz>
It is a dedicated package to WELL pseudo random generators,
which were introduced in Panneton et al. (2006), ``Improved Long-Period
Generators Based on Linear Recurrences Modulo 2'', see <doi:10.1145/1132973.1132974>.
But this package is not intended to be used directly, you are strongly __encouraged__
to use the 'randtoolbox' package, which depends on this package.

Utility functions for working with Random Number Generators
This package contains a set of functions for working with
Random Number Generators (RNGs). In particular, it defines a
generic S4 framework for getting/setting the current RNG, or
RNG data that are embedded into objects for reproducibility.
Notably, convenient default methods greatly facilitate the way
current RNG settings can be changed.

This package contains a set of functions for working with
Random Number Generators (RNGs). In particular, it defines a generic
S4 framework for getting/setting the current RNG, or RNG data
that are embedded into objects for reproducibility.
Notably, convenient default methods greatly facilitate the way current
RNG settings can be changed.

Utility Functions for Working with Random Number Generators
Provides a set of functions for working with
Random Number Generators (RNGs). In particular, a generic
S4 framework is defined for getting/setting the current RNG, or RNG data
that are embedded into objects for reproducibility.
Notably, convenient default methods greatly facilitate the way current
RNG settings can be changed.