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Views:: 4437
Rating:: (32)
Published:: 2019.06.16 06:20
Updated:: 2022.03.15 22:32

\MQL5\Scripts\Random\

pcg_demo.mq5 (5.96 KB) view

pcg_histogram.mq5 (12.24 KB) view

pcg_random_bitmap.mq5 (2.69 KB) view

MathRand_no_bias.mq5 (5.93 KB) view

\MQL5\Include\

Random.mqh (25.26 KB) view

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MathRand() Function

The standard random number generator in MQL has a fairly limited number of possible values from 0 to 32767 (15-bits usable, 2^15 = 32,768 values).

It is classified as linear congruential generator (LCG) which is considered a very basic random number generator.

The implementation of MQL MathRand() can be found here: https://www.mql5.com/en/docs/predefined/_randomseed

This generator has easily detectable statistical flaws which fail most statistical tests of randomness from the PractRand test suite.

For this reason, MathRand() is not suitable for large-scale Monte Carlo simulations or where high-quality randomness is critical.

PCG Random Number Generator

PCG is a family of random number generators, which are fast, statistically excellent, and have small code size.

http://www.pcg-random.org

This class is a wrapper class around the high-quality 32-bits PCG generator. This RNG has an output range of 2^32 which means it can generate 4,294,967,296 possible values.

A permuted congruential generator (PCG) is a pseudorandom number generation algorithm developed in 2014 which applies an output transformation (random shift or rotation) to eliminate the short period problem in the low-order bits that other LCG generators suffer from. It achieves excellent statistical performance with small and fast code, and small state size.

The class provides an easy interface for random number generation.

//+------------------------------------------------------------------+
//| Class CRandom                                                    |
//| Usage: Random number generation using the 32-bit PCG generator.  |
//+------------------------------------------------------------------+
class CRandom
  {
public:
   //--- Constructor and destructor
                CRandom(void);                                       // Constructor (auto-seed)
                CRandom(const ulong initstate,const ulong initseq);  // Constructor (custom seed)
                                                                     
   //--- Methods for generation of random numbers                    
   int          RandomInteger(void);                                 // Random integer [0,2147483648)
   int          RandomInteger(const int max);                        // Random integer [0,max)
   int          RandomInteger(const int min,const int max);          // Random integer [min,max)
                                                                     
   double       RandomDouble(void);                                  // Random double  [0.0,1.0)
   double       RandomDouble(const double max);                      // Random double  [0.0,max)
   double       RandomDouble(const double min,const double max);     // Random double  [min,max)
                                                                     
   bool         RandomBoolean(void);                                 // Random true/false (equal probability)
   bool         RandomBoolean(const double prob_true);               // Random true/false (with prob_true)
                                                                     
   double       RandomNormal(void);                                  // Random double (normal distribution)
   double       RandomNormal(const double mu,const double sigma);    // Random double (normal distribution)
  };