SAFE TOOLBOXES^{®} comes with three highquality random number generators (Mersenne Twister, RanLux and Generalized Feedback Shift Register Generator), two low discrepancy sequences (FaurÃ© and Halton) and one procedure to generate alternate uniform random numbers (antithetic simulation).
The usage of uniform number generators is at the core of running Monte Carlo Simulations. By using the appropriate uniform random number generator you can do a variety of things, such as:
Some usages of uniform random number generators can be seen in the following examples:
A 
B 
C 
D 

1 
Sample from a normal distribution 
0.49 
=sRAND_Normal(0,1) 

2 
Sample from a normal distribution using RanLux uniform random generator with a seed number 123 
1.32 
=sRAND_Normal(0,1, sRAND_Uniform_RanLuxHighQuality(123)) 

3 
Sample from a normal distribution using a Halton Sequence 
1.25 
=sRAND_Normal(0,1, sRAND_Uniform_HaltonSequence(1,1000)) 

4 
Sample from a normal distribution using an antithetic uniform number 
0.49 
=sRAND_Normal(0,1, sRAND_Uniform_Antithetic(1000)) 

5 
Sample from a bivariate normal distribution with a correlation of 0.5. 
0.55 
=sRAND_Normal (0,1,B8) 

6 

0.30 
=sRAND_Normal (0,1,C8) 

7 




8 
Uniform correlated random numbers. 
0.35 
0.22 

9 


={sRAND_Uniform_Correlated(B10:C11)} 
Note: After entering this formula, click on the MVF button. 
10 
Correlation matrix 
1 
0.5 

11 

0.5 
1 

Please note that sequentially generated uniform numbers  as numbers generated using a seed or low discrepancy sequences  can be restarted using the clear memory button .