STK_SAMPLING_NESTEDDESIGN generates a nested design

 CALL: X = stk_sampling_nesteddesign (N, DIM)

   generates a nested design with length(N) levels, with N(k) points at
   the k-th level. X has sum(N) rows and (DIM + 1) columns, the last
   column begin the levels.
   A design is nested when all points at the (k+1)-th level are also at
   the k-th level.

 CALL: X = stk_sampling_nesteddesign (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.
   Default value for BOX: [0; 1]^DIM.
   If BOX is provided, DIM = size(BOX, 2).
   Warning: size(X, 2) == (DIM + 1)

 CALL: X = stk_sampling_nesteddesign (N, DIM, BOX, NITER)

   allows to change the number of independent random LHS that are used,
   when generating a maximin LHS.
   Default value for NITER: 1000. 

 CALL: X = stk_sampling_nesteddesign (N, DIM, BOX, NITER, LEVELS)

   does the same thing, but the levels are indexed by the vector LEVELS.
   The length of LEVELS must be greater or equal than the length of N.
   Default value for levels: 1:length(N).

 EXAMPLE

   n = [30, 14, 5, 2]; dim = 2;
   bnd = stk_hrect([-5, 1; 7, 2]);
   levels = [100; 50; 33; 25; 20;];
   x = stk_sampling_nesteddesign(n, dim, bnd, [], levels);

 REFERENCE

   [1] Loic Le Gratiet, "Multi-fidelity Gaussian process regression for
       computer experiments", PhD thesis, Universite Paris-Diderot -
       Paris VII, 2013.

 See also: stk_sampling_nestedlhs, stk_sampling_maximinlhs