Based on data of real user-agent strings, we can set filtering conditions
    and randomly sample user-agent strings from the user-agent string pool.

Generates random walks of various types by providing a set of functions
    that are compatible with the 'tidyverse'. The functions provided in the package
    make it simple to create random walks with a variety of properties, such as
    how many simulations to run, how many steps to take, and the distribution of
    random walk itself.

Carry out principal component analysis (PCA) of very large pedigrees such as found
    in breeding populations! This package exploits sparse matrices and randomised
    linear algebra to deliver a gazillion-times speed-up compared to naive singular value decoposition (SVD)
    (and eigen decomposition).

Performs random projection using Johnson-Lindenstrauss (JL) Lemma (see William B.Johnson and Joram Lindenstrauss (1984) <doi:10.1090/conm/026/737400>). Random Projection is a dimension reduction technique, where the data in the high dimensional space is projected into the low dimensional space using JL transform. The original high dimensional data matrix is multiplied with the low dimensional projection matrix which results in reduced matrix. The projection matrix can be generated using the projection function that is independent to the original data. Then finally apply the classification task on the projected data.

Provides several non parametric randomness tests for numeric sequences.

Provides (1) pseudo random generators - general linear congruential generators, 
    multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister
    algorithm (<doi:10.1007/978-3-540-74496-2_36>) and WELL (<doi:10.1145/1132973.1132974>) 
    generators); (2) quasi random generators - the Torus algorithm, the
    Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some
    generator tests - the gap test, the serial test, the poker test, see, e.g., 
    Gentle (2003) <doi:10.1007/b97336>. 
    Take a look at the Distribution task view of types and tests of random number generators.
    The package can be provided without the 'rngWELL' dependency on demand.
    Package in Memoriam of Diethelm and Barbara Wuertz.