Pseudo random numbers are need to simulate "random walks" and other stochastic/markoc processes.
The code is *not* a simulation. It produces a PRNG (using LCG algo) that can drive the rest of your script / simulation
Notes:
/////////////////////////////////////////////////////////////////////////////
//
// Generates a pseudo RNG uniformly distributed between your upper and lower bound.
// Please drop me a note if you use the code in original or modified form.
// Inspiration and support from 4X4good .... check out his scripts
//
// Specs:
// Implementation of LCG, using "Numerical Recipes" parameter set (m,a,c)
// as described in wiki article (09/2018):
// https://en.wikipedia.org/wiki/Linear_congruential_generator
//
// Disclaimer:
// The PRNG is provided "as-is" for educational purposes. The LCG algo passes tests for randomness.
// This implementation/script has *not* been tested. Use at your own risk.
//
/////////////////////////////////////////////////////////////////////////////
The code is *not* a simulation. It produces a PRNG (using LCG algo) that can drive the rest of your script / simulation
Notes:
/////////////////////////////////////////////////////////////////////////////
//
// Generates a pseudo RNG uniformly distributed between your upper and lower bound.
// Please drop me a note if you use the code in original or modified form.
// Inspiration and support from 4X4good .... check out his scripts
//
// Specs:
// Implementation of LCG, using "Numerical Recipes" parameter set (m,a,c)
// as described in wiki article (09/2018):
// https://en.wikipedia.org/wiki/Linear_congruential_generator
//
// Disclaimer:
// The PRNG is provided "as-is" for educational purposes. The LCG algo passes tests for randomness.
// This implementation/script has *not* been tested. Use at your own risk.
//
/////////////////////////////////////////////////////////////////////////////