Q: How can I generate random numbers with a normal or Gaussian distribution?
A: There are a number of ways of doing this.
#include <stdlib.h> #include <math.h> #define NSUM 25 double gaussrand() { double x = 0; int i; for(i = 0; i < NSUM; i++) x += (double)rand() / RAND_MAX; x -= NSUM / 2.0; x /= sqrt(NSUM / 12.0); return x; }(Don't overlook the sqrt(NSUM / 12.) correction, though it's easy to do so accidentally, especially when NSUM is 12.)
#include <stdlib.h> #include <math.h> #define PI 3.141592654 double gaussrand() { static double U, V; static int phase = 0; double Z; if(phase == 0) { U = (rand() + 1.) / (RAND_MAX + 2.); V = rand() / (RAND_MAX + 1.); Z = sqrt(-2 * log(U)) * sin(2 * PI * V); } else Z = sqrt(-2 * log(U)) * cos(2 * PI * V); phase = 1 - phase; return Z; }
#include <stdlib.h> #include <math.h> double gaussrand() { static double V1, V2, S; static int phase = 0; double X; if(phase == 0) { do { double U1 = (double)rand() / RAND_MAX; double U2 = (double)rand() / RAND_MAX; V1 = 2 * U1 - 1; V2 = 2 * U2 - 1; S = V1 * V1 + V2 * V2; } while(S >= 1 || S == 0); X = V1 * sqrt(-2 * log(S) / S); } else X = V2 * sqrt(-2 * log(S) / S); phase = 1 - phase; return X; }
References:
Knuth Sec. 3.4.1 p. 117
Box and Muller, ``A Note on the Generation of Random Normal Deviates''
Marsaglia and Bray, ``A Convenient Method for Generating Normal Variables''
Abramowitz and Stegun, Handbook of Mathematical Functions
Press et al., Numerical Recipes in C Sec. 7.2 pp. 288-290