STK: a Small (Matlab/Octave) Toolbox for Kriging
 STK_SAMPLING_SOBOL generates points from a Sobol sequence

 CALL: X = stk_sampling_sobol (N, D)

    computes the first N terms of a D-dimensional Sobol sequence (with
    N < 2^32 and D <= 1111).  The sequence is generated using the algorithm
    of Bratley and Fox [1], as modified by Joe and Kuo [3].

 CALL: X = stk_sampling_sobol (N, DIM, BOX)
  
    does the same thing in the DIM-dimensional hyperrectangle specified by the
    argument BOX, which is a 2 x DIM matrix where BOX(1, j) and BOX(2, j) are
    the lower- and upper-bound of the interval on the j^th coordinate.
     
 CALL: X = stk_sampling_sobol (N, D, BOX, DO_SKIP)

    skips an initial segment of the Sobol sequence  if DO_SKIP is true.  More
    precisely, according to the recommendation of [2] and [3], a number of
    points equal to the largest power of 2 smaller than n is skipped.  If
    DO_SKIP is false, the beginning of the sequence is returns, as in the
    previous cases (in other words, DO_SKIP = false is the default).

 NOTE: Implementation

    The C implementation under the hood is due to Steven G. Johnson, and
    was borrowed from the NLopt toolbox [4] (version 2.4.2).

 REFERENCE

    [1] Paul Bratley and Bennett L. Fox, "Algorithm 659: Implementing Sobol's
        quasirandom sequence generator",  ACM Transactions on Mathematical
        Software, 14(1):88-100, 1988.

    [2] Peter Acworth, Mark Broadie and Paul Glasserman, "A Comparison of Some
        Monte Carlo and Quasi Monte Carlo Techniques for Option Pricing", in
        Monte Carlo and Quasi-Monte Carlo Methods 1996, Lecture Notes in
        Statistics 27:1-18, Springer, 1998.

    [3] Stephen Joe and Frances Y. Kuo, "Remark on Algorithm 659: Implementing
        Sobol's Quasirandom Sequence Generator', ACM Transactions on
        Mathematical Software, 29(1):49-57, 2003.

    [4] Steven G. Johnson, The NLopt nonlinear-optimization package,
        http://ab-initio.mit.edu/nlopt.

 SEE ALSO: stk_sampling_halton_rr2