Returns a matrix of random integers, \(0 ≤ y < 2^{32}-1\), and the state of the random number generator.


{ y, newstate } = rndKMi(r, c, state)#
  • r (scalar) – row dimension.

  • c (scalar) – column dimension.

  • state (scalar or 500x1 vector) –

    scalar case

    state = starting seed value only. If -1, GAUSS computes the starting seed based on the system clock.

    500x1 vector case

    state = the state vector returned from a previous call to one of the rndKM random number functions.

  • y (RxC matrix) – Random integers between \(0\) and \(2^{32} - 1\), inclusive.

  • newstate (500x1 vector) – the updated state.


This example generates two thousand vectors of random integers, each with one million elements. The state of the random number generator after each iteration is used as an input to the next generation of random numbers.

state = 13;
n = 2000;
k = 1000000;
c = 0;
min = 2^32+1;
max = -1;

do while c < n;
   { y,state } = rndKMi(k, 1, state);
   min = minc(min | minc(y));
   max = maxc(max | maxc(y));
   c = c + k;

print "min " min;
print "max " max;


r and c will be truncated to integers if necessary.

Technical Notes#

rndKMi() generates random integers using a KISS+Monster algorithm developed by George Marsaglia. KISS initializes the sequence used in the recur-with-carry Monster random number generator.

See also

Functions rndKMn(), rndKMu()