Download and read datasets from the Swiss National
     Science Foundation (SNF, FNS, SNSF; <https://snf.ch>).  The
     package is lightweight and without dependencies.  Downloaded
     data can optionally be cached, to avoid repeated downloads of
     the same files.  There are also utilities for comparing
     different versions of datasets, i.e. to report added, removed
     and changed entries.

Consolidated data simulation, sample size calculation and
    analysis functions for several snSMART (small sample sequential,
    multiple assignment, randomized trial) designs under one library.  See
    Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian
    analysis of small n sequential multiple assignment randomized trials
    (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732
    <doi:10.1002/sim.7900>.

Identifies single nucleotide variants in next-generation sequencing data by estimating their local false discovery rates. For more details, see Karimnezhad, A. and Perkins, T. J. (2024) <doi:10.1038/s41598-024-51958-z>.

Allows objects to be stored on disc and automatically
       		recalled into memory, as required, by delayed assignment.

Creates stratum orthogonal arrays (also known as strong orthogonal arrays). These are arrays with more levels per column than the typical orthogonal array, and whose low order projections behave like orthogonal arrays, when collapsing levels to coarser strata. Details are described in Groemping (2022) "A unifying implementation of stratum (aka strong) orthogonal arrays" <http://www1.bht-berlin.de/FB_II/reports/Report-2022-002.pdf>.

Provides a fast and efficient implementation of Sobol sequences
    for quasi-Monte Carlo methods. The Sobol sequence is a low-discrepancy
    sequence with the property that for all values of N, its subsequence
    x1, ..., xN has a low discrepancy. It can be used to generate
    quasi-random numbers for use in Monte Carlo integration and other
    simulation methods. This implementation is based on the algorithms
    described by Bratley and Fox (1988) <doi:10.1145/42288.214372> and
    uses direction numbers from Joe and Kuo (2008) <doi:10.1145/1358628.1358630>.
    The package includes both batch and incremental interfaces with support
    for arbitrary starting indices and reproducible sequences. It uses 'Rcpp'
    for efficient 'C++' integration.