LINEAR RANDOM NUMBER GENERATOR WITH COLLATZ TRANSFORMATION FUNCTION
For the first time, a statistical model of a pseudo-random number generator (PRNG) with the Collatz transformation function is constructed and investigated in this paper. The PRNG is implemented in the Python statistical programming environment, and the function is obtained using the inverse transformation method. It is established that the probability integral function takes the form of a transcendental polynomial of quadratic nature, within which the range of PRNG values is justified.